Statistical Inference

Problem 901

This question: 1 point(\$) possible
Of the 94 participants in a drug trial who were given a new experimental treatment for arthritis, 54 showed improvement. Of the 89 participants given a placebo, 46 showed improvement. Construct a two-way table for these data, and then use a 0.05 significance level to test the claim that improvement is independent of whether the participant was given the drug or a placebo.
Click the icon to view the critical values of $\chi^{2}$ table.
Complete the following two-way table. \begin{tabular}{|l|c|} \hline & improvement \\ \hline Drug & $\square$ \\ \hline Placebo & $\square$ \\ \hline \end{tabular} a. State the null and the al A. The null hypothesis The alternative hyp B. The alternative hyThe null hypothesis b. Assuming independenc
Critical values of chi-square \begin{tabular}{|c|c|c|} \hline \multicolumn{3}{|c|}{Critical Values of $\chi^{2}$ : Reject $H_{0}$ Only If $\chi^{2}>$ Critical Value} \\ \hline \multirow[t]{2}{*}{Table size (rows $\times$ columns)} & \multicolumn{2}{|l|}{Significance level} \\ \hline & 0.05 & 0.01 \\ \hline $2 \times 2$ & 3.841 & 6.635 \\ \hline $2 \times 3$ or $3 \times 2$ & 5.991 & 9.210 \\ \hline $3 \times 3$ & 9.488 & 13.277 \\ \hline $2 \times 4$ or $4 \times 2$ & 7.815 & 11.345 \\ \hline $2 \times 5$ or $5 \times 2$ & 9.488 & 13.277 \\ \hline \end{tabular}
Placebo (Round to the nearest hun c. Find the value of the $\chi^{2}$
Print Done $\chi^{2}=$ $\square$ (Round to the ne d. Use the given significance level to find the $\chi^{2}$ critical value.
The critical value is $\square$ . (Round to the nearest thousandth as needed.) e. Using the given significance level, complete the test of the claim that the two variables are independent. State the conclusion that addresses the original claim. Choose the correct answer below. There does not appear to be a relationship between improvement and treatment (drug or placebo).

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Problem 902

$\text{Given the following data points:}$ \begin{align} &\text{Shoe size (pointure de Soulier): 6, Foot length (longueur du pied): 20, Height (hauteur): 146.5} \\ &\text{Shoe size (pointure de Soulier): 6.5, Foot length (longueur du pied): 24, Height (hauteur): 162} \\ &\text{Shoe size (pointure de Soulier): 7, Foot length (longueur du pied): 22.5, Height (hauteur): 163} \\ &\text{Shoe size (pointure de Soulier): 7, Foot length (longueur du pied): 23, Height (hauteur): 166} \\ &\text{Shoe size (pointure de Soulier): 7, Foot length (longueur du pied): 18, Height (hauteur): 169} \\ &\text{Shoe size (pointure de Soulier): 7, Foot length (longueur du pied): \text{unknown}, Height (hauteur): \text{unknown}} \end{align}
$\text{Using a linear model, predict the height for the last data point with a shoe size of 7.}$
$\text{Determine whether interpolation or extrapolation is used in this prediction.}$

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Problem 903

Valerie's team of 30 rated her as "outstanding" at $83\%$ . Why might this result be biased? Choose 1 answer: A, B, C, or D.

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Problem 904

An employment information service claims the mean annual salary for senior level product engineers is $\$ 99,000$ . The annual salaries (in dollars) for a random sample of 16 senior level product engineers are shown in the table to the right. At $\alpha=0.05$ , test the claim that the mean salary is $\$ 99,000$ . Complete parts (a) through (e) below. Assume the population is normally \begin{tabular}{|rrrr|} \hline \multicolumn{4}{|c|}{ Annual Salaries } \\ \hline & & & \\ 100,721 & 96,352 & 93,492 & 112,654 \\ & & & \\ & & & \\ 82,506 & 74,216 & 76,957 & 80,939 \\ 102,543 & 76,238 & 103,925 & 104,037 \\ 91,066 & 82,017 & 85,015 & 110,330 \\ \hline \end{tabular} distributed. (a) Identify the claim and state $\mathrm{H}_{0}$ and $\mathrm{H}_{\mathrm{a}}$ . $\mathrm{H}_{0}: \mu=99000$ $\mathrm{H}_{\mathrm{a}}: \mu$ $\mu$ (Type integers or decimals. Do not round.) The claim is the null hypothesis. (b) Use technology to find the critical value(s) and identify the rejection region(s).
The critical value(s) is/are $t_{0}=$ $\square$ . (Use a comma to separate answers as needed. Round to two decimal places as needed.)

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Problem 905

An employment information service claims the mean annual salary for senior level product engineers is $\$ 99,000$ . The annual salaries (in dollars) for a random sample of 16 senior level product engineers are shown in the table to the right. At $\alpha=0.05$ , test the claim that the mean salary is $\$ 99,000$ . Complete parts (a) through (e) below. Assume the population is normally distributed. \begin{tabular}{|rrrr|} \hline \multicolumn{4}{|c|}{ Annual Salaries } \\ \hline & & \\ 100,721 & 96,352 & 93,492 & 112,654 \\ & & & \\ & & & \\ 82,506 & 74,216 & 76,957 & 80,939 \\ 102,543 & 76,238 & 103,925 & 104,037 \\ 91,066 & 82,017 & 85,015 & 110,330 \\ \hline \end{tabular} A. B. c. D. (c) Find the standardized test statistic, t .
The standardized test statistic is $t=$ $\square$ $\square$ . (Round to two decimal places as needed.)

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Problem 906

\begin{tabular}{|c||c|c|c|c|c|c|c|} \hline \begin{tabular}{c} $t$ \\ (in seconds) \end{tabular} & 0.1 & 0.5 & 0.9 & 1.5 & 1.9 & 2.3 & 2.6 \\ \hline \begin{tabular}{c} $H(t)$ \\ (in meters) \end{tabular} & 1.4 & 5.7 & 8.4 & 9.6 & 8.4 & 5.6 & 2.5 \\ \hline \end{tabular}
1. Justin Tucker, the kicker for the Baltimore Ravens, is considered one of the greatest kickers in NFL history. On a recent kickoff, the height of the ball, in meters, was measured for selected times. This data is shown in the table above. a) Based on this situation and the data presented in the table, would a linear, quadratic, or cubic function be most appropriate to model this data? Give a reason for your answer. b) Find the appropriate regression function to model these data. c) Using the model found in part $b$ , what is the predicted height of the football, in meters, at tine $t=1.3$ seconds?

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Problem 907

At least $68 \%$ of phone numbers in a certain city are unlisted. Express the null and alternative hypotheses in symbolic form for this claim (enter as a percentage). $H_{0}: p$ $\square$ $H_{1}: p$ $\square$ Use the following codes to enter the following symbols: $\begin{array}{l} \geq \text { enter >= } \\ \vdots \text { enter <= } \\ \text { ‡ enter != } \end{array}$

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Problem 908

From a random sample of 51 adults who earned an associate's degree from a community college (but no education beyond), the mean lifetime earnings was $\$ 1.6$ million. The sample standard deviation was $\$ 0.5$ million. Construct a $95 \%$ confidence interval for the mean lifetime income of adults who earned an associate's degree and no formal education beyond.
A What type of inference problem is this? (iii) Confidence interval for a population mean (ii) Confidence interval for the population mean of paired differences (iii) Confidence interval for a population proportion (iv) Confidence interval for the difference in two population proportions
B Are the criteria for approximate normality met? Explain. Random sample C Compute the margin of error. Round to three decimal places. $140,627$
D Compute the lower limit and upper limit of the $95 \%$ confidence interval. Round to three decimal places. $\text { Lower Limit }=1,459,373 \quad \text { Upper Limit }=1,740,627$
E Interpret the confidence interval in the context of this situation.

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Problem 909

Evaluate the following formula for $\bar{x}_{1}=2.39, \bar{x}_{2}=2.63, s_{1}=0.97, s_{2}=0.63, n_{1}=30$ , and $n_{2}=37$ $t=\frac{\bar{x}_{1}-\bar{x}_{2}}{\sqrt{\frac{s_{1}^{2}}{n_{1}}+\frac{s_{2}^{2}}{n_{2}}}}$ $\square$ (Round to two decimal places as needed.)

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Problem 910

Evaluate the following formula for $\bar{x}_{1}=27.6106, \bar{x}_{2}=25.9487, \mu_{1}-\mu_{2}=0, s_{1}=43.83, s_{2}=43.83, n_{1}=40$ , and $n_{2}=43$ . $t=\frac{\left(\bar{x}_{1}-\bar{x}_{2}\right)-\left(\mu_{1}-\mu_{2}\right)}{\sqrt{\frac{s_{1}^{2}}{n_{1}}+\frac{s_{2}^{2}}{n_{2}}}}$ $t=$ $\square$ (Round to two decimal places as needed.)

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Problem 911

On veut déterminer la relation entre la spécialisation d'un diplômé en aḋministration et le secteur d'emploi où il travaille. L'étude porte sur un échantillon aléatoire de 200 sujets et le tableau suivant représente les données observées. \begin{tabular}{lcccc} & \multicolumn{4}{c}{ Spécialisation } \\ Secteur \\ D'emploi & Comptabilité & Finance & Marketing & Gestion \\ \cline { 2 - 5 } & 10 & 4 & 12 & 14 \\ Fabrication & 11 & 8 & 14 & 17 \\ Service & 2 & 3 & 44 & 21 \\ Vente au détall & 7 & 15 & 10 & 8 \\ Autre & & & & \end{tabular}
Est-ce que la spécialisation d'un diplômé en administration influence significativement son secteur d'emploi?
1. Écrivez vos hypothèses HO et H 1
2. Calculez les effectifs théoriques.
3. Calculez le khi-carré et comparez à la valeur dans la table pour un niveau de test de $5 \%$ .
4. Concluez de façon précise et complête.
Note: Une conclusion de type H0 doit rester neutre, une conclusion de type H1 doit être affirmative et suivie d'une analyse de la dépendance entre les deux variables.

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Problem 912

and after the diesel exhaust exposure. The resulting data are given in the accompanying table. For purposes of this exercise, assume that the sample of 10 men is representative of healthy adult males. \begin{tabular}{|c|c|c|c|c|} \hline \multirow{2}{*}{ Subject } & \multicolumn{4}{|c|}{ MPF (in Hz) } \\ \cline { 2 - 5 } & Location 1 before & Location 1 after & Location 2 before & Location 2 after \\ \hline 1 & 6.4 & 8.0 & 6.8 & 9.4 \\ \hline 2 & 8.6 & 12.7 & 9.5 & 11.2 \\ \hline 3 & 7.4 & 8.4 & 6.6 & 10.2 \\ \hline 4 & 8.6 & 9.0 & 9.0 & 9.7 \\ \hline 5 & 9.9 & 8.4 & 9.6 & 9.2 \\ \hline 6 & 7.8 & 11.0 & 9.0 & 11.8 \\ \hline 7 & 7.4 & 14.4 & 7.8 & 9.3 \\ \hline 8 & 6.7 & 7.3 & 7.1 & 8.0 \\ \hline 10 & 8.8 & 11.2 & 7.4 & 9.3 \\ \hline \end{tabular}
Use a table or technology. Round your answers to two decimal places.) ( 081 , 315 ) Hz

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Problem 913

From a random sample of 80 women, 48 say they have been sexually harassed. From another random sample of 65 men, 13 say they have been sexually harassed. Construct a $99 \%$ confidence interval for the difference between the proportions of women and men who say they have been sexually harassed.

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Problem 914

PREVIOUS ANSWERS ASK YOUR TEACHER PRACTICE ANOTHER \begin{tabular}{|c|c|c|c|c|} \hline \multirow{2}{*}{Subject} & \multicolumn{4}{|c|}{MPF (in Hz)} \\ \hline & Location 1 before & Location 1 after & Location 2 before & Location 2 after \\ \hline 1 & 6.4 & 8.0 & 6.8 & 9.4 \\ \hline 2 & 8.6 & 12.7 & 9.5 & 11.2 \\ \hline 3 & 7.4 & 8.4 & 6.6 & 10.2 \\ \hline 4 & 8.6 & 9.0 & 9.0 & 9.7 \\ \hline 5 & 9.9 & 8.4 & 9.6 & 9.2 \\ \hline 6 & 8.8 & 11.0 & 9.0 & 11.8 \\ \hline 7 & 9.1 & 14.4 & 7.8 & 9.3 \\ \hline 8 & 7.4 & 11.1 & 8.1 & 9.1 \\ \hline 9 & 6.7 & 7.3 & 7.2 & 8.0 \\ \hline 10 & 8.8 & 11.2 & 7.4 & 9.3 \\ \hline \end{tabular}
Use a table or technology. Round your answers to two decimal places.) (-2 $\square$ $-251$ $\square$ 6.69 ) Hz

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Problem 915

(Note if any boxes seem not applicable, leave blank.) A random sample of 130 business executives was classified according to age and the degree of risk aversion as measured by a psychological test.
Degree of Risk Aversion \begin{tabular}{|c|c|c|c|c|} \hline Age & \multicolumn{3}{|c|}{ Low } & Medium \\ High & Total \\ \hline Below 45 & 14 & 22 & 7 & 43 \\ \hline $45-55$ & 16 & 33 & 12 & 61 \\ \hline Over 55 & 4 & 15 & 7 & 26 \\ \hline Total & & & & 130 \\ \hline \end{tabular}
Do these data demonstrate an association between risk aversion and age?
Test Statistic: $\square$ According to your table, the P -value is bounded by: .50 $\square$ Is there sufficient evidence to demonstrate an association between

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Problem 916

Step 3 All the necessary values have been found to calculate the margin of error. We have $z_{\alpha / 2}=1.960, \bar{p}=0.557$ four decimal places. $\begin{aligned} E & =z_{\alpha / 2} \sqrt{\frac{\bar{p}(1-\bar{p})}{n}} \\ & =1.960 \sqrt{\frac{0.5571(1-0.5571)}{359}} \\ & =\square \end{aligned}$ Submit Skip_(you cannot come back) Submit Answer

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Problem 917

You wish to test the following claim $\left(H_{1}\right)$ at a significance level of $\alpha=0.002$ . $\begin{array}{l} H_{0}: \mu=70.1 \\ H_{1}: \mu<70.1 \end{array}$
You obtain a sample mean of $\bar{x}=68.3$ , and sample standard deviation of $s=20.4$ for a sample of size $n=45$ . a. The test statistic $(t)$ for the data $=$ $\square$ (Please show your answer to three decimal places.) b. The $p$ -value for the sample = $\square$ (Please show your answer to four decimal places.) c. The $p$ -value is...

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Problem 918

Survey a group of people with 2 questions about marital status and number of times eating out per month. \begin{tabular}{lllll} & \multicolumn{4}{l}{ Eat out per Month } \\ & $21-30$ & $31-40$ & $41-50$ & TOTAL \\ Single & 3 & 8 & 9 & 20 \\ Married & 8 & 7 & 5 & 20 \\ Widowed & 8 & 10 & 15 & 33 \\ Divorced & 9 & 8 & 15 & 32 \\ TOTAL & 28 & 33 & 44 & 105 \end{tabular}
Question \#4: at $\alpha=0.05$ , find the $p$ -value Your answer (with 4 decimal places) -->

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Problem 919

Follow the link Least Squares Line. This will direct you to a spreadsheet download that may be useful for checking your work for the exercise. Astronomer Edwin Hubble postulated a relationship between the distance between Earth and the velocity at which a galaxy appears to be traveling away from Earth. The following table shows observations of seven galaxies. Distance is measured in megaparsecs ( 1 Mpc is approximately 3,260 light-years), and velocity is measured in kilometers per second. \begin{tabular}{|c|c|} \hline Distance (Mpc) & Velocity (km/s) \\ \hline 51.8 & 4,560 \\ \hline 12.2 & 1,184 \\ \hline 27.1 & 1,736 \\ \hline 46.2 & 3,807 \\ \hline 58.2 & 5,168 \\ \hline 46.2 & 3,807 \\ \hline 29.1 & 1,714 \\ \hline \end{tabular} (a) Find the equation of linear regression line for the data where distance is the independent variable, $x$ , and velocity is the dependent variable. (Round your numerical answers to two decimal places.) $\hat{y}=\square$ (b) Using the equation from part (a), estimate the velocity (in kilometers per second) at which a galaxy 130 Mpc from Earth is traveling. (Round your answer to the nearest whole number.) $\qquad$ $\mathrm{km} / \mathrm{s}$

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Problem 920

12.3 Performing Linear Regressions with Technology
1. An economist is trying to understand whether there is a strong link between CEO pay ration and corporate revenue. The economist gathers data, including the CEO pay ratio and the corporate revenue for 10 companies for a particular year. The pay ratio data is reported by the companies themselves and represents the ratio of CEO compensation to the median employee salary. The data has been reproduced in the table below. Corporate Revenue (million \$) \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline CEO & 286 & 944 & 321 & 268 & 183 & 309 & 132 & 264 & 236 & 259 \\ \hline Revenue & 21,973 & 29,846 & 38,507 & 18,912 & 25,947 & 97,023 & 35,888 & 59,131 & 60,579 & 27,242 \\ \hline \end{tabular} a) What is the equation of the line of best fit? b) What is "r "and determine if it is a strong, moderate, or weak correlation.

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Problem 921

www. helpyourmath.com is an OER website to help students to save money on textbooks and homework systems. A survey of 24 randomly selected students finds that they save a mean of $\$ 86$ per semester by using www.helpyourmath.com. Assume the date comes from a normal distribution and the sample standard deviation is $\$ 19$ per month.
Confidence Interval: What is the $95 \%$ confidence interval to estimate the population mean? Round your answers to two decimal places. $\square$

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Problem 922

The least-squares regression equation is $\hat{y}=762.7 x+13,048$ where $y$ is the median income and $x$ is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7285 . Complete parts (a) through (d). (a) Predict the median income of a region in which $30 \%$ of adults 25 years and older have at least a bachelor's degree. \ $35929 (Round to the nearest dollar as needed.) (b) In a particular region, 29.6 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is$ \ $38,860$ . Is this income higher than what you would expect? Why?
This is higher than expected because the expected income is $\$ 35,624$ (Round to the nearest dollar as needed.) (c) Interpret the slope. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or decimal. Do not round.) A. For $0 \%$ of adults having a bachelor's degree, the median income is predicted to be $\$$ $\square$ . B. For every dollar increase in median income, the percent of adults having at least a bachelor's degree is $\square$ $\%$ , on average. C. For a median income of $\$ 0$ , the percent of adults with a bachelor's degree is $\square$ \%. D. For every percent increase in adults having at least a bachelor's degree, the median income increases by $\$$ $\square$ , on average.

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Problem 923

Question 6, 9.1.15 HW Score: $55.56 \%, 5$ of 9 points .1
Construct a $90 \%$ confidence interval of the population proportion using the given information. $x=125, n=250$
Click here to view the table of critical values.
The lower bound is $\square$ The upper bound is $\square$ (Round to three decimal places as needed. Table of critical values \begin{tabular}{ccc} \begin{tabular}{c} Level of Confidence, \\ $(\mathbf{1}-\alpha) \cdot \mathbf{1 0 0} \%$ \end{tabular} & Area in Each Tail, $\frac{\boldsymbol{\alpha}}{\mathbf{2}}$ & Critical Value, $\boldsymbol{z}_{\frac{\boldsymbol{\alpha}}{\mathbf{2}}}$ \\ \hline $90 \%$ & 0.05 & 1.645 \\ \hline $95 \%$ & 0.025 & 1.96 \\ \hline $99 \%$ & 0.005 & 2.575 \\ \hline \end{tabular} Print Done

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Problem 924

\begin{problem} The governor of a state has put together a team tasked with determining factors that account for the number of children living in poverty within the state. The team wants to know if the number of children living in poverty in a town is proportional to the population of the town, so they look at the population and number of children in poverty for 10 towns in the state. The data is reported in the table below.
\begin{center} \begin{tabular}{|c|c|} \hline Population & Children in Poverty \\ \hline 41,788 & 992 \\ 8,767 & 41 \\ 59,376 & 702 \\ 2,920 & 17 \\ 2,862 & 31 \\ 16,344 & 114 \\ 9,099 & 170 \\ 92,513 & 1,239 \\ 10,354 & 105 \\ 31,705 & 625 \\ \hline \end{tabular} \end{center}
\begin{enumerate} \item[(a)] What is the equation of the line of best fit? \item[(b)] What is " $r$ " and determine if it is a strong, moderate, or weak correlation. \end{enumerate} \end{problem}

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Problem 925

To test $H_{0}: \mu=100$ versus $H_{1}: \mu \neq 100$ , a simple random sample size of $n=20$ is obtained from a population that is known to be normally distributed. Answer parts (a)-(d).
Click here to view the t-Distribution Area in Right Tail. (a) If $\bar{x}=105.3$ and $s=8.3$ , compute the test statistic. $\mathrm{t}=$ $\square$ (Round to three decimal places as needed.)

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Problem 926

Firstborn \begin{tabular}{lllll} \hline 99 & 116 & 103 & 123 & 110 \\ 104 & 94 & 92 & 82 & 85 \\ \hline \end{tabular} \begin{tabular}{lllll} \hline \multicolumn{4}{c}{ Secondborn } \\ \hline 103 & 96 & 120 & 120 & 123 \\ 99 & 110 & 99 & 101 & 108 \\ \hline \end{tabular} Send data to Excel
Part: $0 / 2$
Part 1 of 2
Construct a 99.8\% confidence interval for the difference in mean IQ between firstborn and secondborn sons. Let $\mu_{1}$ denote the mean IQ of the firstborn sons. Use tables to find the critical value and round the answers to at least one decimal place.
A 99.8\% confidence interval for the difference in mean IQ between firstborn and secondborn sons is $\square$

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Problem 927

Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places) \begin{tabular}{|c|c|} \hline $x$ & $y$ \\ \hline 3 & 27.61 \\ \hline 4 & 29.88 \\ \hline 5 & 29.95 \\ \hline 6 & 31.32 \\ \hline 7 & 34.89 \\ \hline 8 & 35.06 \\ \hline \end{tabular}

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Problem 928

Select the appropriate word or phrase to complete the sentence.
The number of degrees of freedom for the Student's $t$ -test of a population mean is always 1 less than the (Choose one) $\nabla$ .

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Problem 929

Question 12, Question Points: 0 of 1 Save
About $33 \%$ of the population in a large region are between the ages of 40 and 65 , according to the country's census. However, only $3 \%$ of the 2900 employees at a company in the region are between the ages of 40 and 65 . Lawyers are concerned that the company is engaging in age discrimination, not hiring enough people in the age group 40 to 65 . Assume the number of employees inthis compnay is a sample. Check whether the conditions for using the one-proportion $z$ -test are met.
Are all the conditions satisfied? Select all that apply. A. No, the Large Population condition is not satisfied or cannot be reasonably assumed. B. No, the Independence condition is not satisfied or cannot be reasonably assumed. C. No, the Large Sample Size condition is not satisfied or cannot be reasonably assumed. D. No, the Random Sample condition is not satisfied or cannot be reasonably assumed. E. Yes, all conditions are satisfied or can be reasonably assumed.

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Problem 930

Do students perform the same when they take an exam alone as when they take an exam in a classroom setting? Eight students were given two tests of equal difficulty. They took one test in a solitary room and they took the other in a room filled with other students. The results are shown below.
Exam Scores \begin{tabular}{|c|c|c|c|c|c|c|c|c|} \hline Alone & 77 & 80 & 78 & 84 & 89 & 86 & 86 & 67 \\ \hline Classroom & 81 & 83 & 90 & 89 & 92 & 89 & 82 & 69 \\ \hline \end{tabular}
Assume a Normal distribution. What can be concluded at the the $\alpha=0.05$ level of significance level of significance?
For this study, we should use Select an answer a. The null and alternative hypotheses would be: $H_{0}$ : Select an answer Select an answer Select an answer
⓪ (please enter a decimal) $H_{1}$ : Select an answer Select an answer Select an answer (t) (Please enter a decimal) b. The test statistic ? $=$ $\square$ (please show your answer to 3 decimal places.) c. The $p$ -value $=$ $\square$ (Please show your answer to 4 decimal places.) d. The $p$ -value is $\square$ $\alpha$ e. Based on this, we should Select an answer $\square$ $\square$ the null hypothesis. f. Thus, the final conclusion is that ... The results are statistically significant at $\alpha=0.05$ , so there is sufficient evidence to conclude that the eight students scored the same on average taking the exam alone compared to the classroom setting. The results are statistically insignificant at $\alpha=0.05$ , so there is statistically significant evidence to conclude that the population mean test score taking the exam alone is equal to the population mean test score taking the exam in a classroom setting. The results are statistically insignificant at $\alpha=0.05$ , so there is insufficient evidence to conclude that the population mean test score taking the exam alone is not the same as the population mean test score taking the exam in a classroom setting. The results are statistically significant at $\alpha=0.05$ , so there is sufficient evidence to conclude that the population mean test score taking the exam alone is not the same as the population mean test score taking the exam in a classroom setting.

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Problem 931

The 'pizza connection' is the principle that the price of a slice of pizza is always about the same as the subway fare. Use the pizza and subway cost data in the table below to determine whether there is a linear correlation between these two items. Construct a scatterplot, find the value of the linear correlation coefficient r , and find the P -value of r . Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that the subway fare is always about the same as a slice of pizza? Use a significance level of $\alpha=0.05$ .
Click here for data on pizza costs and subway fares over the years.
Construct a scatterplot. Choose the correct graph below. A. B. c. D.
Determine the linear correlation coefficient. The linear correlation coefficient is $\mathrm{r}=$ .729 $\square$ (Round to three decimal places as needed.) Pizza Cost and Subway Fares \begin{tabular}{|lcccccccccc|c|} \hline Year & 1960 & 1973 & 1986 & 1995 & 2002 & 2003 & 2009 & 2013 & 2015 & 2019 & a \\ Pizza Cost & 0.15 & 0.35 & 1.00 & 1.25 & 1.75 & 2.00 & 2.25 & 2.30 & 2.75 & 3.00 \\ Subway Fare & 0.15 & 0.30 & 0.95 & 1.40 & 1.50 & 2.05 & 2.25 & 2.50 & 2.75 & 2.70 \\ CPI & 29 & 43.9 & 109.7 & 152.1 & 180.0 & 184.0 & 214.5 & 233.0 & 237.0 & 252.2 \\ \hline \end{tabular}

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Problem 932

The 'pizza connection' is the principle that the price of a slice of pizza is always about the same as the subway fare. Use the pizza and subway cost data in the table below to determine whether there is a linear correlation between these two items. Construct a scatterplot, find the value of the linear correlation coefficient r , and find the P -value of r . Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that the subway fare is always about the same as a slice of pizza? Use a significance level of $\alpha=0.05$ .
Click here for data on pizza costs and subway fares over the years.
Construct a scatterplot. Choose the correct graph below. A. B. C. D.
Determine the linear correlation coefficient. The linear correlation coefficient is $r=0.987$ . (Round to three decimal places as needed.) Determine the null and alternative hypotheses. $\begin{array}{l} H_{0}: \rho=0 \\ H_{1}: \rho \neq 0 \end{array}$ (Type integers or decimals. Do not round.) Pizza Cost and Subway Fares \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|c|} \hline Year & 1960 & 1973 & 1986 & 1995 & 2002 & 2003 & 2009 & 2013 & 2015 & 2019 & 맘 \\ \hline Pizza Cost & 0.15 & 0.35 & 1.00 & 1.25 & 1.75 & 2.00 & 2.25 & 2.30 & 2.75 & 3.00 & \\ \hline Subway Fare & 0.15 & 0.30 & 0.95 & 1.40 & 1.50 & 2.05 & 2.25 & 2.50 & 2.75 & 2.70 & \\ \hline CPI & 29 & 43.9 & 109.7 & 152.1 & 180.0 & 184.0 & 214.5 & 233.0 & 237.0 & 252.2 & \\ \hline \end{tabular}

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Problem 933

6.2.6. A random sample of size 16 is drawn from a normal distribution having $\sigma=6.0$ for the purpose of testing $H_{0}: \mu=30$ versus $H_{1}: \mu \neq 30$ . The experimenter chooses to define the critical region $C$ to be the set of sample means lying in the interval (29.9, 30.1). What level of significance does the test have? Why is $(29.9,30.1)$ a poor choice for the critical region? What range of $\bar{y}$ values should comprise $C$ , assuming the same $\alpha$ is to be used?

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Problem 934

The line of best fit and the correlation coefficient are calculated for a set of data. The value of the correlation coefficient is $r=0.10$ . What is the strength and type of the correlation for this data? A) weak and negative B) weak and positive C) strong and negative D) strong and positive

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Problem 935

A test is made of $H_{0}: \mu=53$ versus $H_{1}: \mu<53$ . A sample of size 37 is drawn. The sample mean and standard deviation are $\bar{x}=44$ and $s=11$ .
Part 1 of 3 (a) Compute the value of the test statistic $t$ . Round your answer to two decimal places.
The value of the test statistic is $t=-4.98$ . $\square$
Part: $1 / 3$
Part 2 of 3 (b) Is $H_{0}$ rejected at the $\alpha=0.05$ level?
We (Choose one) $\boldsymbol{\nabla}$ the null hypothesis.

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Problem 936

The average salary for American college graduates is $\$ 48,400$ . You suspect that the average is more for graduates from your college. The 53 randomly selected graduates from your college had an average salary of $\$ 51,937$ and a standard deviation of $\$ 9,140$ . What can be concluded at the $\alpha=0.05$ level of significance? a. For this study, we should use Select an answer b. The null and alternative hypotheses would be: $H_{0}$ : ? 웅 Select an answer 0 $\square$ $H_{1}$ : ? . 0 Select an answer $\square$ c. The test statistic ? ${ }^{0}=$ $\square$ (please show your answer to 4 decimal places.) d. The $p$ -value $=$ $\square$ (Please show your answer to 4 decimal places.) e. The $p$ -value is $\square$ $\alpha$ f. Based on this, we should Select an answer the null hypothesis. g. Thus, the final conclusion is that ... The data suggest that the sample mean is not significantly greater than 48,400 at $\alpha=0.05$ , so there is statistically insignificant evidence to conclude that the sample mean salary for graduates from your college is greater than 51,937 . The data suggest that the population mean is not significantly greater than 48,400 at $\alpha=$ 0.05 , so there is statistically insignificant evidence to conclude that the population mean salary for graduates from your college is greater than 48,400. The data suggest that the populaton mean is significantly greater than 48,400 at $\alpha=0.05$ , so there is statistically significant evidence to conclude that the population mean salary for graduates from your college is greater than 48,400 . h. Interpret the $p$ -value in the context of the study. There is a $0.34187113 \%$ chance of a Type I error. If the population mean salary for graduates from your college is $\$ 48,400$ and if another 53 graduates from your college are surveyed then there would be a $0.34187113 \%$ chance that the population mean salary for graduates from your college would be greater than $\$ 48,400$ . If the population mean salary for graduates from your college is $\$ 48,400$ and if another 53 graduates from your college are surveyed then there would be a $0.34187113 \%$ chance that the sample mean for these 53 graduates from your college surveyed would be greater than \ $51,937. There is a$ 0.34187113 \% $chance that the population mean salary for graduates from your college is greater than$ \ $48,400$ .

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Problem 937

HW 14 Score: 0/9 Answered: 0/9
Question 1
You intend to conduct an ANOVA with 5 groups in which each group will have the same number of subjects: $n=22$ . (This is referred to as a "balanced" single-factor ANOVA.)
What are the degrees of freedom for the numerator? d.f. (treatment) = $\square$ What are the degrees of freedom for the denominator? d.f. (error) = $\square$ Submit Question

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Problem 938

We poll 450 people and find that $40 \%$ favor Candidate S. In order to estimate with $90 \%$ confidence the percent of ALL voters would vote for Candidate S, we should use: 2-SampZInt 2-PropZInt TInterval 1-PropZInt 2-SampTInt ZInterval

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Problem 939

We wish to estimate what percent of adult residents in a certain county are parents. Out of 600 adult residents sampled, 468 had kids. Based on this, construct a $90 \%$ confidence interval for the proportion p of adult residents who are parents in this county:
Express your answer in tri-inequality form. Give your answers as decimals, to three places. $\square$ $<\mathrm{p}<$ $\square$ Express the same answer using the point estimate and margin of error. Give your answers as decimals, to three places. $p=$ $\square$ $\pm$ $\square$

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Problem 940

Answer the following True or False: A researcher hypothesizes that the average student spends less than $20 \%$ of their total study time reading the textbook. The appropriate hypothesis test is a left tailed test for a population mean. false true

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Problem 941

The average American gets a haircut every 43 days. Is the average smaller for college students? The data below shows the results of a survey of 13 college students asking them how many days elapse between haircuts. Assume that the distribution of the population is normal. $48,35,36,33,41,49,47,49,29,46,38,42,40$
What can be concluded at the the $\alpha=0.10$ level of significance level of significance? a. For this study, we should use Select an answer b. The null and alternative hypotheses would be: $H_{0}$ : ? 0 Select an answer $H_{1}$ : ? $\square$ Select an answer $\square$ c. The test statistic ? $\square$ $=$ $\square$ (please show your answer to 3 decimal places.) d. The $p$ -value $=$ $\square$ (Please show your answer to 3 decimal places.) e. The $p$ -value is ? $\square$ $\alpha$ f. Based on this, we should Select an answer $\square$ 0 숭 $\square$ : g. Thus, the final conclusion is that ... The data suggest the populaton mean is significantly lower than 43 at $\alpha=0.10$ , so there is sufficient evidence to conclude that the population mean number of days between haircuts for college students is lower than 43. The data suggest the population mean number of days between haircuts for college students is not significantly lower than 43 at $\alpha=0.10$ , so there is insufficient evidence to conclude that the population mean number of days between haircuts for college students is lower than 43. The data suggest the population mean is not significantly lower than 43 at $\alpha=0.10$ , so there is sufficient evidence to conclude that the population mean number of days between haircuts for college students is equal to 43.

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Problem 942

Name: Jerald Bollingsley
1. (Section 6.2) A researcher wonders if final exams raise the stress level of college-freshmen. Under normal circumstances, the average systolic blood pressure of healthy college-freshman is 120 with a standard deviation of 12. During final's week, the researcher tests 30 college-freshmen just before their Statistics Final Exam. She determines their average blood pressure is 123.2 . What should she conclude? Set up and test an appropriate hypothesis test using level of significance $\alpha=0.05$ . [Note: The units for systolic blood pressure are " mm HG" (millimeters of mercury].

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Problem 943

2. (Section 6.3) [Testing Binomial Data]
Ｙou may want to begin this problem by writing down the definition of $\alpha]$ . Suppose the null-hypothesis $H_{0}: p=0.7$ is tested against the alternative-hypothesis $H_{1}: p<0.7$ using a small sample size of $n=7$ . If the decision rule is to "Reject $H_{0}$ if $k \leq 3$ ", then what is the test's level of significance $\alpha$ ?

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Problem 944

Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in ${ }^{\circ} \mathrm{F}$ . Find the regression equation, letting chirps in 1 minute be the independent ( $x$ ) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Use a significance level of 0.05 . \begin{tabular}{l|cccccccc} Chirps in 1 min & 973 & 752 & 1048 & 973 & 848 & 1071 & 846 & 1128 \\ \hline Temperature ( ${ }^{\circ} \mathrm{F}$ ) & 77.1 & 66 & 86.6 & 83.5 & 73.5 & 85.8 & 76.5 & 83.9 \end{tabular}
The regression equation is $\hat{y}=$ $\square$ $+$ $\square$ $x$ . (Round the $y$ -intercept to one decimal place as needed. Round the slope to four decimal places as needed.)

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Problem 945

In his book Outliers, author Malcolm Gladwell argues that more baseball players have birth dates in the months immediately following July 31 , because that was the age cutoff date for non-school baseball leagues. Here is a sample of frequency counts of months of birth dates of American-born professional baseball players starting with January:384, 329, 357, 348, 339, $312,313,505,412,428,401,362$ . 만 Using a 0.05 significance level, is there sufficient evidence to warrant rejection of the claim that American-born professional baseball players are born in different months with the same frequency? Do the sample values appear to support the author's claim?
Identify the null and alternative hypotheses. Choose the correct answer below. A. $\mathrm{H}_{0}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. $\mathrm{H}_{1}$ : The months immediately following July 31 have different frequencies of American-born professional baseball player birth dates than the other months. B. $\mathrm{H}_{0}$ : Birth dates of American-born professional baseball players occur with the same frequency in all months of the year. $\mathrm{H}_{1}$ : The months immediately following July 31 have different frequencies of American-born professional baseball player birth dates than the other months. C. $\mathrm{H}_{0}$ : Birth dates of American-born professional baseball players occur with the same frequency in all months of the year. $\mathrm{H}_{1}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. D. $H_{0}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. $\mathrm{H}_{1}$ : All months have different frequencies of American-born professional baseball player birth dates.

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Problem 946

In his book Outliers, author Malcolm Gladwell argues that more baseball players have birth dates in the months immediately following July 31 , because that was the age cutoff date for non-school baseball leagues. Here is a sample of frequency counts of months of birth dates of American-born professional baseball players starting with January: 384, 329, 357, 348, 339, $312,313,505,412,428,401,362$ . 믄 Using a 0.05 significance level, is there sufficient evidence to warrant rejection of the claim that American-born professional baseball players are born in different months with the same frequency? Do the sample values appear to support the author's claim?
Identify the null and alternative hypotheses. Choose the correct answer below. A. $\mathrm{H}_{0}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. $\mathrm{H}_{1}$ : The months immediately following July 31 have different frequencies of American-born professional baseball player birth dates than the other months. B. $\mathrm{H}_{0}$ : Birth dates of American-born professional baseball players occur with the same frequency in all months of the year. $H_{1}$ : The months immediately following July 31 have different frequencies of American-born professional baseball player birth dates than the other months. C. $\mathrm{H}_{0}$ : Birth dates of American-born professional baseball players occur with the same frequency in all months of the year. $\mathrm{H}_{1}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. D. $H_{0}$ : At least one month has a different frequency of American-born professional baseball player birth dates than the other months. $H_{1}$ : All months have different frequencies of American-born professional baseball player birth dates. Calculate the test statistic, $\chi^{2}$ . $\chi^{2}=\square$ (Round to two decimal places as needed.)

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Problem 947

12.1 HW Question 29, 12.1.11-T HW Score: 24.57\%, 7.12 of 29 points Save
A certain statistics instructor participates in triathlons. The accompanying table lists times (in minutes and seconds) he recorded while riding a bicycle for five laps through each mile of a 3-mile loop. Use a 0.05 significance level to test the claim that it takes the same time to ride each of the miles. Does one of the miles appear to have a hill?
Click the icon to view the data table of the riding times.
Determine the null and alternative hypotheses. $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}$ $H_{1}$ : At least one of the three population means is different from the others.
Find the F test statistic. $F=$ $\square$ (Round to four decimal places as needed.)
Riding Times (minutes and seconds) \begin{tabular}{llllll} Mile 1 & $3: 15$ & $3: 23$ & $3: 24$ & $3: 22$ & $3: 22$ \\ Mile 2 & $3: 18$ & $3: 21$ & $3: 22$ & $3: 17$ & $3: 20$ \\ Mile 3 & $3: 33$ & $3: 32$ & $3: 28$ & $3: 32$ & $3: 30$ \end{tabular} (Note: when pasting the data into your technology, each mile row will have separate columns for each minute and second entry. You will need to convert each minute/second entry into seconds only.)
Print Done Clear all Check answer

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Problem 948

Answer the questions below. (a) A researcher measured the shoe size and reading ability of a large group of children. He found that, as shoe size increases, so does reading ability. What does his analysis show? There is no correlation between shoe size and reading ability. There is a correlation between shoe size and reading ability. There may or may not be causation. Further studies would have to be done to determine this. There is a correlation between shoe size and reading ability. There is probably also causation. This is because there is an increase in reading ability with an increase in shoe size.

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Problem 949

Use the results from a survey of a simple random sample of 1142 adults. Among the 1142 respondents, $69 \%$ rated themselves as above average drivers. We want to test the claim that more than $\frac{13}{20}$ of adults rate themselves as above average drivers. Complete parts (a) through (e). A. This statement seems to suggest that with a low P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. B. This statement seems to suggest that with a high P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. C. This statement seems to suggest that with a high $P$ -value, the alternative hypothesis has been proven or is supported, but this conclusion cannot be made. D. This statement seems to suggest that with a high P-value, the alternative hypothesis has been rejected, but this conclusion cannot be made. e. Common significance levels are 0.01 and 0.05 . Why would it be unwise to use a significance level with a number like 0.0432 ? A. A significance level with more than 2 decimal places has no meaning. B. Choosing a more specific significance level makes it more difficult to reject the null hypothesis. C. Using a significance level to more decimal places makes calculations of P -values more difficult. D. Choosing such a specific significance level could give the impression that the significance level was carefully chosen to reach a desired conclusion.

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Problem 950

Suppose that shoe sizes of American women have a bell-shaped distribution with a mean of 8.19 and a standard deviation of 1.49 . Using the empirical rule, what percentage of American women have shoe sizes that are no more than 11.17 ? Please do not round your answer.

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Problem 951

Part 4 of 4
Soon after the euro was introduced as a currency in Europe, it was widely reported that someone had spun a euro coin 250 times and gotten he coin. Complete parts a) through c) below. a) Estimate the true proportion of.heads. Use a $90 \%$ confidence interval. Don't forget to check the conditions first.
Are the conditions satisfied? A. The $10 \%$ Condition and the Success/Failure Condition are both met. The Randomization Condition is not met. B. The Randomization Condition and the $10 \%$ Condition are both met. The Success/Failure Condition is not met. C. The Randomization Condition and the Success/Failure Condition are both met. The $10 \%$ Condition is not met. D. The Independence Assumption is not plausible. The $10 \%$ Condition is not met. E. The Randomization Condition is met. Neither the $10 \%$ Condition nor the Success/Failure Condition are met. F. All necessary assumptions and conditions are met.
The 90\% confidence interval is ( $0.468,0.572$ ). (Use ascending order. Round to three decimal places as needed.) b) Does your confidence interval provide evidence that the coin is unfair when spun? Explain.
Since 0.50 is $\square$ within the interval, there $\square$ evidence that the coin is unfair when spun. c) What is the significance level of this test? Explain.
The significance level is $\alpha=$ $\square$ . The test is a(n) $\square$ test based on the 90\% confidence interval above. (Type an integer or a decimal.)

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Problem 952

In a random sample of 8 people, the mean commute time to work was 34.5 minutes and the standard deviation was 7.2 minutes. A $95 \%$ confidence interval using the $t$ -distribution was calculated to be ( 28.5 .40 .5 ). After researching commute times to work, it was found that the population standard deviation is 9.3 minutes. Find the margin of error and construct a $95 \%$ confidence interval using the standard nomal distribution with the appropriate calculations for a standard deviation that is known. Compare the results.
The margin of error of $\mu$ is $\square$ (Round to two decimal places as needed.)

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Problem 953

12.1 HW Part 3 of 5 Points: 0 of 1
The data from car crash tests for four different vehicle size categories (Small, Midsize, Large, and SUV) with measured amounts of left leg femur force (kN) results in the following Minitab display. Using a 0.05 significance level, test the claim that the four vehicle size categories have the same mean force on the femur of the left leg. Does size of the car appear to have an effect on the force on the left femur in crash tests?
Determine the null hypothesis. $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}=\mu_{4}$
Determine the alternative hypothesis. $H_{1}$ : At least one of the means is different from the others Determine the test statistic. The test statistic is $\square$ (Round to two decimal places as needed.) Clear all Check answer

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Problem 954

12.1 HW Question 28, 12.1.9-T Part 3 of 6 Points: 0.25 of 1
Pages were randomly selected from one book each from authors A, B, and C. The accompanying table shows the ease-of-reading scores for those pages. Use a 0.05 significance level to test the claim that pages from books by those three authors have the same mean ease-of-reading score. Given that higher scores correspond to text that is easier to read, which author appears to be different, and how is that author different?
Click the icon to view the data table of the ease-of-reading scores.
Determine the null hypothesis. $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}$
Determine the alternative hypothesis. $H_{1}$ : At least one of the means is different from the others Determine the test statistic. The test statistic is $\square$ $\square$ . (Round to two decimal places as needed.)
Ease-of-Reading Scores \begin{tabular}{|l|l|l|l|l|l|l|l|l|l|} \hline A & 58.9 & 73.8 & 73.7 & 64.1 & 72.3 & 89.1 & 43.1 & 76.4 & 76.6 \\ \hline B & 85.9 & 84.4 & 79.3 & 82.2 & 80.2 & 84.5 & 79.1 & 70.5 & 78.1 \\ \hline C & 69.2 & 64.2 & 71.4 & 71.2 & 68.4 & 51.1 & 72.2 & 74.4 & 52.3 \\ \hline \end{tabular}
Print Done

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Problem 955

Question 9 of 10 (i) point) I Question Attempt 2 of Unilmied
Fast reactions: In a study of reaction times, the time to respond to a visual stimulus $(x)$ and the time to respond to an auditory stimulus ( $y$ ) were recorded for each of 8 subjects. Times were measured in thousandths of a second. The results are presented in the following table. \begin{tabular}{cc} \hline Visual & Auditory \\ \hline 191 & 169 \\ 203 & 206 \\ 201 & 197 \\ 188 & 193 \\ 228 & 209 \\ 161 & 159 \\ 176 & 163 \\ 178 & 201 \\ \hline \end{tabular} Send data to Excel
The least-squares regression line $\hat{y}=b_{0}+b_{1} x=46.9658+0.7348 x$ and $\Sigma(x-\bar{x})^{2}=2915.5000$ are known for this data. Construct a $95 \%$ confidence interval for the slope. Round the answers to at least four decimal places.

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Problem 956

Question 9 of 10 (1 point) I Question Attempt 3 of Unlimited
Fast reactions: In a study of reaction times, the time to respond to a visual stimulus $(x)$ and the time to respond to an auditory stimulus ( $y$ ) were recorded for each of 7 subjects. Times were measured in thousandths of a second. The results are presented in the following table. \begin{tabular}{cc} \hline Visual & Auditory \\ \hline 161 & 159 \\ 176 & 163 \\ 178 & 201 \\ 188 & 193 \\ 201 & 197 \\ 203 & 206 \\ 211 & 189 \\ \hline \end{tabular} Send data to Excel
The least-squares regression line $\hat{y}=b_{0}+b_{1} x=51.2341+0.7203 x$ and $\Sigma(x-\bar{x})^{2}=1895.4286$ are known for this data. Construct a $95 \%$ confidence interval for the slope. Round the answers to at least four decimal places.
The $95 \%$ confidence interval is $\square$ $<\beta_{1}<$ $\square$ 1. Save For Later Submit Assig

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Problem 957

BSAD/MATH 2170 Applied Statistics - Marquis (1) Haley Stone Homework: 10.1 Correlation Question 6, 10.1.1 HW Score: $37.88 \%, 8.33$ of 22 points Part 2 of 3 Points: 0.33 of 1 Save
Question list
Media 3
Question 1
Question 2
Question 3
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Question 5
Twenty different statistics students are randomly selected. For each of them, their body temperature $\left({ }^{\circ} \mathrm{C}\right)$ is measured and their head circumference $(\mathrm{cm})$ is measured. a. For this sample of paired data, what does r represent, and what does $\rho$ represent? b. Without doing any research or calculations, estimate the value of $r$ . c. Does r change if body temperatures are converted to Fahrenheit degrees? A. $r$ is a statistic that represents the proportion of the variation in head circumference that can be explained by variation in body temperature, and $\rho$ is a parameter that represents the value of the linear correlation coefficient that would be computed by using all of the paired data in the population of all statistics students. B. $r$ is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data, and $\rho$ is a parameter that represents the value of the linear correlation coefficient that would be computed by using all of the paired data in the population of all statistics students. C. $r$ is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data, and $\rho$ is a parameter that represents the proportion of the variation in head circumference that can be explained by variation in body temperature. D. $r$ is a parameter that represents the value of the linear correlation coefficient that would be computed by using all of the paired data in the population of all statistics students, and $\rho$ is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data. b. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or a decimal rounded to one decimal place as needed.) The value of $r$ is estimated to be $\square$ because it is likely that body temperature and head circumference are strongly positively correlated. B. The value of $r$ is estimated to be $\square$ , because it is likely that body temperature and head circumference are strongly negatively correlated. C. The value of $r$ is estimated to be $\square$ , because it is likely that there is no correlation between body temperature and head circumference. $x /$ Question 6

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Problem 958

In Oak City, predict how many adults get news from newspapers based on a sample of 50,000. Round to the nearest whole number.

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Problem 959

Use the Grubbs test to check if $0.1189$ is an outlier in the data set $0.1123, 0.1087, 0.1139, 0.1112, 0.1189$ at $95\%$ confidence. Show your calculations.

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Problem 960

Which of the following is/are True? The level of significance of a test depends on the value of the sample statistic. The level of significance depends on the alternative hypothesis. The level of significance is generally set in advance before samples are drawn The level of significance is the probability of rejecting a null hypothesis when it is in fact true.

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Problem 961

Based solely on the information given, do you have reason to question the results of the following hypothetical study? Explain your reasoning.
A study by a conservative foundation is designed to assess a new Democratic spending plan.
Is there reason to question the results? Select all that apply. A. Yes, there is reason. It makes sense that a Democratic spending plan would be studied by a conservative foundation. B. Yes, there is reason. There is a possibility of bias in the study. C. No, there is not reason. The goal of the study is clear. D. No, there is not reason. There is no bias in the study. E. Yes, there is reason. The variables that were measured are not identified. F. No, there is not reason. It is unlikely that there are any confounding variables in the study.

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Problem 962

Good credit: The Fair Isaac Corporation (FICO) credit score is used by banks and other lenders to determine whether someone is a good credit risk. Scores range from 300 to 850 , with a score of 720 or more indicating that a person is a very good credit risk. An economist wants to determine whether the mean FICO score is lower than the cutoff of 720 . She finds that a random sample of 55 people had a mean FICO score of 685 with a standard deviation of 80 . Can the economist conclude that the mean FICO score is less than 720 ? Use the $\alpha=0.10$ level of significance and the $P$ -value method with the TI-84 Plus calculator.
Part: $0 / 5$ $\square$
Part 1 of 5 (a) State the appropriate null and alternate hypotheses. $\begin{array}{l} H_{0}: \square \\ H_{1}: \square \end{array}$
This hypothesis test is a $\square$ (Choose one) test. $\square$ Skip Part Check Save For Later Submit Assignment

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Problem 963

To test $\mathrm{H}_{0}: \mu=50$ versus $\mathrm{H}_{1}: \mu<50$ , a random sample of size $\mathrm{n}=22$ is obtained from a population that is known to be normally distributed. Complete parts (a) through (d) below. Click here to view the t-Distribution Area in Right Tail. (a) If $\bar{x}=47.5$ and $s=10.3$ , compute the test statistic. $t_{0}=$ $\square$ (Round to three decimal places as needed.) (b) If the researcher decides to test this hypothesis at the $\alpha=0.05$ level of significance, determine the critical value(s). Although technology or a t-distribution table can be used to find the critical value, in this problem use the t-distribution table given.
Critical Value: $\square$ (Round to three decimal places. Use a comma to separate answers as needed.) (c) Draw a t-distribution that depicts the critical region. Choose the correct answer below. A. B. c. (d) Will the researcher reject the null hypothesis? A. Yes, because the test statistic falls in the critical region. B. Yes, because the test statistic does not fall in the critical region. Time Remaining: 01:33:36 Submit quiz

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Problem 964

The operations manager of a company hired a consultant to look for possible ways to improve workers' productivity. The plan recommended by the consultant was applied to a sample of workers, whose mean productivity was compared with their mean productivity before the plan was implemented. The resulting p-value was 0.15 . Based on this result, which would be the correct conclusion and course of action? the p -value is less than or equal to the significance level. There is insufficient sample evidence showing that the recommended plan increases workers' productivity. The plan should not be implemented without additional study A paired sample $d$ test should be applied inthis case. There is sufficient sample evidence showing that the recommended plan increases workers' productivity. The plan should be implemented to include all workers

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Problem 965

In a poll of 510 human resource professionals, $45.9 \%$ said that body piercings and tattoos were big personal grooming red flags. Complete parts (a) through (d) below. a. Among the 510 human resource professionals who were surveyed, how many of them said that body piercings and tattoos were big personal grooming red flags? $\square$ (Round to the nearest integer as needed.) b. Construct a 99\% confidence interval estimate of the proportion of all human resource professionals believing that body piercings and tattoos are big personal grooming red flags. $\square$ $<p<$ $\square$ (Round to three decimal places as needed.) c. Repeat part (b) using a confidence level of $80 \%$ . $\square$ < $<<$ $\square$ (Round to three decimal places as needed.) d. Compare the confidence intervals from parts (b) and (c) and identify the interval that is wider. Why is it wider? proportion. proportion. proportion. proportion.

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Problem 966

Let $x$ be a random variable that represents the pH of arterial plasma (i.e., acidity of the blood). For healthy adults, the mean of the $x$ distribution is $\mu=7,4+A$ new drug for arthritis has been developed. However, it is thought that this drug may change blood pH. A random sample of 31 patients with arthritis took the drug for 3 months. Blood tests showed that $\bar{x}=8.6$ with sample standard deviation $s=3.1$ . Use a $5 \%$ level of significance to test the claim that the drug has changed (either way) the mean pH level of the blood. $\Omega$ USE SALT (a) What is the level of significance? $\square$ State the null and alternate hypotheses. (Enter $!=$ for $\neq$ as needed.) $\mathrm{H}_{0}$ : $\square$ $H_{1}$ : $\square$ (b) What sampling distribution will you use? Explain the rationale for your choice of sampling distribution. We'll use the Student's $t$ , since the sample size is large and $\sigma$ is unknown. We'll use the standard normal, since the sample size is large and $\sigma$ is unknown. We'll use the standard normal, since the sample size is large and $\sigma$ is known. We'll use the Student's $t$ , since the sample size is large and $\sigma$ is known.
Compute the appropriate sampling distribution value of the sample test statistic. (Round your answer to two decimal places.) $\square$

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Problem 967

Researchers want to test a new anti-unxicty medication. They split participants into three conditions $(0 \mathrm{mg}, 50 \mathrm{mg}$ , and 100 mg $)$ , then ask them to rate their anciety leyel on a scale of 1-10. Compute the value of the tes suatistic. A) $F=96.33$ B) $F=86.33$ C) $\mathrm{F}=77.33$ D) $\mathrm{F}=67.33$ \begin{tabular}{|l|l|l|} \hline Omg & 50 mg & 100 mg \\ \hline 9 & 7 & 4 \\ \hline 8 & 6 & 3 \\ \hline 7 & 6 & 2 \\ \hline 8 & 7 & 3 \\ \hline 8 & 8 & 4 \\ \hline 9 & 7 & 3 \\ \hline 8 & 6 & 2 \\ \hline \end{tabular}

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Problem 968

ALEKS - Danlette Tah - Learn New Chrom Gmail VouTube Google Docs Login More Section - Resu... Confldence intervals and Hypothesis Testing Danlette Computing and comparing confidence intervals for a population... Espanol
You are looking at a population and are interested in the proportion $p$ that has a certaln characteristic. Unknown to you, this population proportion is $p=0.85$ . You have taken a random sample of size $n=115$ from the population and found that the proportion of the sample that has the characteristic is $\widehat{p}=0.84$ . Your sample is Sample 1 in the table below. (In the table, Sample 1 is written "S1", Sample 2 is written "S2", etc.) (a) Based on Sample 1, graph the $75 \%$ and $90 \%$ confidence intervals for the population proportion. Use 1.150 for the critical value for the $75 \%$ confidence interval, and use 1.645 for the critical value for the $90 \%$ confidence interval. (If necessary, consult a list of formulas.) - Enter the lower and upper limits on the graphs to show each confidence interval. Write your answers with two decimal places. - For the points ( $*$ and $\bullet$ ), enter the population proportion, 0.85 . ? 凅 ■ 回 (4) (b) Press the "Generate Samples" button below to simulate taking 19 more samples of size $n=115$ from the same population. Notice that the confidence intervals for these samoles are drawn automaticallv, Then complete parts (c) and ( $d$ ) below the table. Explanation Check

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Problem 969

Question 1
A car dealership claims that there is a difference in the mean credit scores of customers who buy cars in the first quarter of the fiscal year and those who buy cards in the last quarter of the fiscal year. The results of a random survey of 298 customers from the first quarter of the fiscal year and 246 customers from the last quarter of the fiscal year are shown below. The two samples are independent. Do the results support the dearlership's claim? Use alpha $=0.05$ . \begin{tabular}{|c|c|} \hline First Quarter & Last Quarter \\ \hline $n_{1}=298$ & $n_{2}=246$ \\ \hline $\bar{x}_{1}=561$ & $\bar{x}_{2}=570$ \\ \hline $\sigma_{1}=51$ & $\sigma_{2}=50$ \\ \hline \end{tabular} a. Given the alternative hypothesis, the test is Select an answer $\vee$ b. Determine the test statistic. Round to two decimal places. test statistic $=$ $\square$ c. Find the critical value(s). If there are two, just input the positive critical value. critical value $=$ $\square$ d. Make a decision. Reject the null hypothesis. Fail to reject the null hypothesis.

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Problem 970

Use a $t$ -distribution to find a confidence interval for the difference in means $\mu_{d}=\mu_{1}-\mu_{2}$ using the relevant sample results from paired data. Assume the results come from random samples from populations that are approximately normally distributed, and that differences are computed using $d=x_{1}-x_{2}$ .
A 95\% confidence interval for $\mu_{d}$ using the paired data in the following table: \begin{tabular}{l|ll} \hline Case & \begin{tabular}{l} Situation \\ 1 \end{tabular} & \begin{tabular}{l} Situation \\ 2 \end{tabular} \\ \hline 1 & 78 & 86 \\ 2 & 80 & 85 \\ 3 & 95 & 90 \\ 4 & 62 & 78 \\ 5 & 71 & 78 \\ 6 & 72 & 62 \\ 7 & 84 & 88 \\ 8 & 91 & 92 \\ \hline \end{tabular}
Give the best estimate for $\mu_{d}$ , the margin of error, and the confidence interval. Enter the exact answer for the best estimate, and round your answers for the margin of error and the confidence interval to two decimal places. best estimate $=$ $\square$ $-3.5$ margin of error = $\square$ $\square$ $-6.71$
The $95 \%$ confidence interval is to i 3.21 $\square$

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Problem 971

The effectiveness of a blood-pressure drug is being investigated. An experimenter finds that, on average, the reduction in systolic blood pressure is 53.4 for a sample of size 714 and standard deviation 17.2 .
Estimate how much the drug will lower a typical patient's systolic blood pressure (using a $99 \%$ confidence level).
Enter your answer as a tri-linear inequality accurate to one decimal place (because the sample statistics are reported accurate to one decimal place). $\square$ $<\boldsymbol{\mu}<$ $\square$ Answer should be obtained without any preliminary rounding.

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Problem 972

d. The $p$ -value $=$ 0.0735 $\qquad$ (Please show your answer to 4 decimal places.) e. The $p$ -value is $\square$ $\alpha$ f. Based on this, we should fail to reject
0 the null hypothesis. g. Thus, the final conclusion is that ... The data suggest the populaton proportion is significantly smaller than $53 \%$ at $\alpha=0.05$ , so there is sufficient evidence to conclude that the population proportion of students who played intramural sports who received a degree within six years is smaller than $53 \%$ The data suggest the population proportion is not significantly smaller than $53 \%$ at $\alpha=0.05$ , so there is not sufficient evidence to conclude that the population proportion of students who played intramural sports who received a degree within six years is smaller than $53 \%$ . The data suggest the population proportion is not significantly smaller than $53 \%$ at $\alpha=0.05$ , so there is sufficient evidence to conclude that the population proportion of students who played intramural sports who received a degree within six years is equal to $53 \%$ . h. Interpret the p-value in the context of the study. If the population proportion of students who played intramural sports who received a degree within six years is $53 \%$ and if another 257 students who played intramural sports are surveyed then there would be a $10.1 \%$ chance fewer than $49 \%$ of the 257 students surveyed received a degree within six years. There is a 53\% chance of a Type I error. If the sample proportion of students who played intramural sports who received a degree within six years is $49 \%$ and if another 257 such students are surveyed then there would be a $10.1 \%$ chance of concluding that fewer than $53 \%$ of all students who played intramural sports received a degree within six years. There is a $10.1 \%$ chance that fewer than $53 \%$ of all students who played intramural sports graduate within six years. i. Interpret the level of significance in the context of the study. If the population proportion of students who played intramural sports who received a degree within six years is $53 \%$ and if another 257 students who played intramural sports are surveyed then there would be a $5 \%$ chance that we would end up falsely concluding that the proportion of all students who played intramural sports who received a degree within six years is smaller than 53\% There is a $5 \%$ chance that the proportion of all students who played intramural sports who received a degree within six years is smaller than $53 \%$ . If the population proportion of students who played intramural sports who received a degree within six years is smaller than $53 \%$ and if another 257 students who played intramural sports are surveyed then there would be a $5 \%$ chance that we would end up falsely concluding that the proportion of all students who played intramural sports who received a degree within six years is equal to $53 \%$ . There is a $5 \%$ chance that aliens have secretly taken over the earth and have cleverly disguised themselves as the presidents of each of the countries on earth.

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Problem 973

g. Thus, the final conclusion is that ... The data suggest the population proportion is not significantly larger $60 \%$ at $\alpha=0.05$ , so there is sufficient evidence to conclude that the proportion of voters who prefer the Democratic candidate is equal to $60 \%$ . The data suggest the population proportion is not significantly larger $60 \%$ at $\alpha=0.05$ , so there is not sufficient evidence to conclude that the proportion of voters who prefer the Democratic candidate is larger 60\%. - The data suggest the populaton proportion is significantly larger $60 \%$ at $\alpha=0.05$ , so there is sufficient evidence to conclude that the proportion of voters who prefer the Democratic candidate is larger 60\% h. Interpret the p-value in the context of the study. There is a $0.33 \%$ chance that more than $60 \%$ of all voters prefer the Democratic candidate. - If the population proportion of voters who prefer the Democratic candidate is $60 \%$ and if another 222 voters are surveyed then there would be a $0.33 \%$ chance that more than $69 \%$ of the 222 voters surveyed prefer the Democratic candidate.
O If the sample proportion of voters who prefer the Democratic candidate is $69 \%$ and if another 222 voters are surveyed then there would be a $0.33 \%$ chance of concluding that more than $60 \%$ of all voters surveyed prefer the Democratic candidate. There is a $0.33 \%$ chance of a Type I error. i. Interpret the level of significance in the context of the study. If the population proportion of voters who prefer the Democratic candidate is $60 \%$ and if another 222 voters are surveyed then there would be a $5 \%$ chance that we would end up falsely concluding that the proportion of voters who prefer the Democratic candidate is larger 60\% There is a $5 \%$ chance that the proportion of voters who prefer the Democratic candidate is larger 60\%. There is a $5 \%$ chance that the earth is flat and we never actually sent a man to the moon. If the proportion of voters who prefer the Democratic candidate is larger 60\% and if another 222 voters are surveyed then there would be a $5 \%$ chance that we would end up falsely concluding that the proportion of voters who prefer the Democratic candidate is equal to $60 \%$ .

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Problem 974

Question 4
Score on last try: 0.4 of 1 pts. See Details for more. Next question You can retry this question below
Fill in the missing values for this ANOVA summary table: \begin{tabular}{|c|c|c|c|c|c|c|} \hline & S.S. & \multicolumn{2}{|c|}{d.f.} & & M.S. & F \\ \hline Between & & 7 & $\checkmark$ & & & 3.353 \\ \hline Within & 2325 & 93 & $\checkmark$ & 2 & & \\ \hline TOTAL & & 100 & & & & \\ \hline \end{tabular}
Submit Question

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Problem 975

A survey of 2279 adults in a certain large country aged 18 and older conducted by a reputable polling organization found that 421 have donated blood in the past two years. Complete parts (a) through (c) below. Click here to view the standard normal distribution table (page 1). Click here to view the standard normal distribution table (page 2). $\hat{p}=0.185$ (Round to three decimal places as needed.) (b) Verify that the requirements for constructing a confidence interval about p are satisfied.
The sample $\square$ a simple random sample, the value of $\hat{p}(1-\hat{p})$ is $\square$ , which is $\square$ $\square$ less than or equal to $5 \%$ of the $\square$ (Round to three decimal places as needed.) (c) Construct and interpret a 90\% confidence interval for the population proportion of adults in the country who have donated blood in the past two years. Select the correct choice below and fill in any answer boxes within your choice. (Type integers or decimals rounded to three decimal places as needed. Use ascending order.) A. There is a $\square$ \% probability the proportion of adults in the country aged 18 and older who have donated blood in the past two years is between $\square$ and $\square$ . B. We are $\square$ \% confident the proportion of adults in the country aged 18 and older who have donated blood in the

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Problem 976

ter 9 Homework Question 5, 9.2.1
Determine whether the samples are independent or dependent. A data set includes the morning and evening temperature for the last 120 days.
Choose the correct answer below. A. The samples are dependent because there is not a natural pairing between the two samples, B. The samples are independent because there is not a natural pairing between the two samples. C. The samples are independent because there is a natural pairing between the two samples. D. The samples are dependent because there is a natural pairing between the two samples.

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Problem 977

Which of the following statements are true concerning the mean of the differences between two dependent samples (matched pairs)?
Select all that apply. A. If one has more than 9 matched pairs of sample data, one can consider the sample to be large and there is no need to check for normality. B. The methods used to evaluate the mean of the differences between two dependent variables apply if one has 92 weights of taxpayers from Ohio and 92 weights of taxpayers from Texas. C. The requirement of a simple random sample is satisfied if we have independent pairs of convenience sampling data. D. If one has twenty matched pairs of sample data, there is a loose requirement that the twenty differences appear to be from a normally distributed population. E. If one wants to use a confidence interval to test the claim that $\mu_{d}>0$ with a 0.05 significance level, the confidence interval should have a confidence level of $90 \%$ .

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Problem 978

(40) صحة اعتّاد صاحب المصنع من عدمه عند مستوى الدلالة الإجابة:

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Problem 979

Since an instant replay system for tennis was introduced at a major tournament, men challenged 1384 referee calls, with the result that 431 of the calls were overturned. Women challenged 762 referee calls, and 212 of the calls were overturned. Use a 0.01 significance level to test the claim that men and women have equal success in challenging calls. Complete parts (a) through (c) below. a. Test the claim using a hypothesis test.
Consider the first sample to be the sample of male tennis players who challenged referee calls and the second sample to be the sample of female tennis players who challenged referee calls. What are the null and alternative hypotheses for the hypothesis test? A. $H_{0}: p_{1} \leq p_{2}$ B. $H_{0}: p_{1} \geq p_{2}$ C. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1} \neq p_{2}$ $H_{1}: p_{1} \neq p_{2}$ D. $H_{0}: p_{1}=p_{2}$ E. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1}<p_{2}$ $H_{1}: P_{1}>P_{2}$ $H_{1}: p_{1} \neq p_{2}$ F. $H_{0}: p_{1} \neq p_{2}$ $H_{1}: p_{1}=p_{2}$

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Problem 980

Since an instant replay system for tennis was introduced at a major tournament, men challenged 1384 referee calls, with the result that 431 of the calls were overturned. Women challenged 762 referee calls, and 212 of the calls were overtumed. Use a 0.01 significance level to test the claim that men and women have equal success in challenging calls. Complete parts (a) through (c) below. a. Test the claim using a hypothesis test.
Consider the first sample to be the sample of male tennis players who challenged referee calls and the second sample to be the sample of female tennis players who challenged referee calls. What are the null and alternative hypotheses for the hypothesis test? A. $H_{0}: p_{1} \leqslant p_{2}$ $H_{1}: p_{1} \neq p_{2}$ D. $H_{0}: P_{1}=p_{2}$ $H_{1}: P_{1}>P_{2}$ B. $H_{0}: p_{1} \geq p_{2}$ $H_{1}: p_{1} \neq p_{2}$ E. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1} \neq p_{2}$ C. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1}<p_{2}$ F. $H_{0}: p_{1} \neq p_{2}$ $H_{1}: p_{1}=p_{2}$ Identify the test statistic. $z=$ $\square$ (Round to two decimal places as needed.)

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Problem 981

Dark Chocolate for Good Health A study ${ }^{1}$ examines chocolate's effects on blood vessel function in healthy people. In the randomized, double-blind, placebo-controlled study, 11 people received 46 grams ( 1.6 ounces) of dark chocolate (which is naturally flavonoid-rich) every day for two weeks, while a control group of 10 people received a placebo consisting of dark chocolate with low flavonoid content. Participants had their vascular health measured (by means of flow-mediated dilation) before and after the two-week study. The increase over the two-week period was measured, with larger numbers indicating greater vascular health. For the group getting the good dark chocolate, the mean . increase was 1.3 with a standard deviation of 2.32 , while the control group had a mean change of -0.96 with a standard deviation of 1.58. ${ }^{1}$ Engler, M., et. al., "Flavonoid-rich dark chocolate improves endothelial function and increases plasma epicatechin concentrations in healthy adults," Journal of the American College of Nutrition, 2004 Jun; 23(3): 197-204.
Part 1 (a) Find a $95 \%$ confidence interval for the difference in means between the two groups $\mu_{C}-\mu_{N}$ , where $\mu_{C}$ represents the mean increase in flow-mediated dilation for people eating dark chocolate every day and $\mu_{N}$ represents the mean increase in flowmediated dilation for people eating a dark chocolate substitute each day. You may assume that neither sample shows significant departures from normality.
Round your answers to two decimal places. The 95\% confidence interval is $\square$ to i .

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Problem 982

Split the Bill?
A study compared the cost of restaurant meals when people pay individually versus splitting the bill as a group. In the experiment half of the people were told they would each be responsible for individual meals costs and the other half were told the cost would be split equally among the six people at the table. The data in SplitBill includes the cost of what each person ordered (in Israeli shekels) and the payment method (Individual or Split). Some summary statistics are provided in the table below and both distributions are reasonably bell-shaped. Use this information to test (at a $5 \%$ level) if there is evidence that the mean cost is higher when people split the bill. \begin{tabular}{|l|ccc|} \hline Payment & Sample size & Mean & Std. dev. \\ \hline Individual & 24 & 37.29 & 12.54 \\ \hline Split & 24 & 50.92 & 14.33 \\ \hline \end{tabular}
Table 1: Cost of meals by payment type
Let group 1 and group 2 be the costs in the Individual and Split situations, respectively.
Click here for the dataset associated with this question.
Part 1
Part 2
Calculate the relevant test statistic. Round your answer to two decimal places. $t$ -statistic $=$

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Problem 983

A study was conducted to determine the proportion of people who dream in black and white instead of color. Among 323 people over the age of 55,72 dream in black and white, and among 289 people under the age of 25,16 dream in black and white. Use a 0.05 significance level to test the claim that the proportion of people over 55 who dream in black and white is greater than the proportion for those under 25. Complete parts (a) through (c) below. a. Test the claim using a hypothesis test.
Consider the first sample to be the sample of people over the age of 55 and the second sample to be the sample of people under the age of 25 . What are the null and alternative hypotheses for the hypothesis test? A. $H_{0}: P_{1}=P_{2}$ B. $H_{0}: p_{1}=p_{2}$ C. $H_{0}: p_{1} \leq p_{2}$ $H_{1}: p_{1} \neq p_{2}$ $H_{1}: p_{1}>p_{2}$ $H_{1}: p_{1} \neq p_{2}$ D. $H_{0}: p_{1}=p_{2}$ E. $H_{0}: p_{1} \geq p_{2}$ $H_{1}: P_{1}<P_{2}$ $\mathrm{H}_{1}: \mathrm{p}_{1} \neq \mathrm{p}_{2}$ F. $H_{0}: p_{1} \neq p_{2}$ $H_{1}: p_{1}=p_{2}$
Identify the test statistic. $\mathrm{z}=\square$ (Round to two decimal places as needed.)

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Problem 984

Anna Bischoff 12/03/24 10:44 AM Question 13, 9.1.33-T Part 2 of 4 HW Score: $66.33 \%, 9.29$ of 14 points Points: 0 of 1 Save
The weights (in pounds) of eight vehicles and the variabilities of their braking distances (in feet) when stopping on a dry surface are shown in the table. At $\alpha=0.05$ , is there enough evidence to conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? \begin{tabular}{|l|c|c|c|c|c|c|c|c|} \hline Weight, $\mathbf{x}$ & 5910 & 5360 & 6500 & 5100 & 5890 & 4800 & 5700 & 5870 \\ \hline Variability, $\mathbf{y}$ & 1.72 & 1.99 & 1.92 & 1.55 & 1.69 & 1.50 & 1.57 & 1.70 \\ \hline \end{tabular}
Setup the hypothesis for the test. $\begin{array}{l} H_{0}: \rho=0 \\ H_{a}: \rho \neq 0 \end{array}$
Calculate the test statistic. $\mathrm{t}=3.33$ (Round to two decimal places as needed.)

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Problem 985

atistical Methods I FONO5 Deshaunte scales 12/03/24 1:01 PM उHW Question 2, 8.1.5 HW Score: 2.86\%, 0.8 of 28 points Part 2 of 2 Points: 0 of 1 Save
Claim: More than $4.5 \%$ of homes have only a landline telephone and no wireless phone. Sample data: A survey by the National Center for Health Statistics showed that among 16,063 homes $5.79 \%$ had landline phones without wireless phones. Complete parts (a) and (b). a. Express the original claim in symbolic form. Let the parameter represent a value with respect to homes that have only a landline telephone and no wireless phone. p 0.045 (Type an integer or a decimal. Do not round.) b. Identify the null and alternative hypotheses. $\begin{array}{l|} \mathrm{H}_{0}: \\ \mathrm{H}_{1}: \\ : \bar{\nabla} \\ \square \end{array}$ (Type integers or decimals. Do not round.) w an example Get more help - Clear all Check answer

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Problem 986

Question 16, 8.2.1 Pait 1 of 3 HW Scores 43.33\%, 12.13 of 28 points Points: 0 of 1 Save
Use the results from a survey of a simple random sample of 1229 adults. Among the 1229 respondents, $71 \%$ rated themselves as above average drivers. We want to test the claim that $\frac{13}{20}$ of adults rate themselves as above average drivers. Complete parts (a) through (c). a. Identify the actual number of respondents who rated themselves as above average drivers. $\square$ (Round to the nearest whole number as needed.) nore help - Clear all Check answer

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Problem 987

```latex A health organization would like to determine if there is a difference in COVID mean recovery times between individuals who are 30 years old or younger and individuals who are older than 30 years old. The organization randomly selects 45 individuals who are 30 years old or younger who recovered from COVID and 50 individuals who are older than 30 years old who recovered from COVID-19. The table below summarizes the sample results for each group:
\begin{tabular}{|l|l|l|l|} \hline & Sample Size & Mean & Standard Deviation \\ \hline 30 years old or younger & 45 & 13 \text{ days} & 15 \text{ days} \\ \hline Older than 30 years Old & 50 & 3 \text{ days} & 2 \text{ and } 3 \text{ days} \\ \hline \end{tabular}
Test the claim that there is a difference in COVID mean recovery times between individuals who are 30 years old or younger and individuals who are older than 30 years old at a 5\% significance level.
D. State the null and alternative hypothesis.
E. State the P-value.
F. State your conclusion.

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Problem 988

n 10 of 16 Side-by-Side
A research firm supplies manufacturers with estimates of the sales of their products from samples of stores. Marketing managers often look at the sales estimates and ignore sampling error. An SRS of 50 stores this month shows mean sales of 41 units of a particular appliance with standard deviation of 11 units. During the same month last year, an SRS of 52 stores gave mean sales of 38 units of the same appliance with a standard deviation of 13 units. An increase from 38 to 41 is a rise of $7.9 \%$ . The marketing manager is happy because sales are up $7.9 \%$ . (a) Give a $95 \%$ confidence interval for the difference in mean number of units of the appliance sold at all retail stores. Give your answers to three decimal places. lower bound: $\square$ upper bound: $\square$

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Problem 989

A poll of 1019 Americans showed that $46.5 \%$ of the respondents prefer to watch the news rather than read or listen to Use those results with a 0.05 significance level to test the claim that fewer than half of Americans prefer to watch the news rather than read or listen to it. Use the P-value method. Use the normal distribution as an approximation to the binomial distribution.
Let $p$ denote the population proportion of all Americans who prefer to watch the news rather than read or listen to it. Identify the null and alternative hypotheses. $\begin{array}{l} \mathrm{H}_{0}: \mathrm{p} \square \\ \mathrm{H}_{1} \mathrm{p} \end{array}$ (Type integers or decimals. Do not round.)

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Problem 990

Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor ( x ) variable. Find the best predicted tip for a ride that takes 22 minutes. How does the result compare to the actual tip amount of $\$ 5.05$ ? Use a significance level of 0.05 . \begin{tabular}{l|cccccccc} Distance & 1.02 & 0.68 & 1.32 & 2.47 & 1.40 & 1.80 & 8.51 & 1.65 \\ \hline Time & 8.00 & 6.00 & 8.00 & 18.00 & 18.00 & 25.00 & 31.00 & 11.00 \\ \hline Fare & 7.80 & 6.30 & 7.80 & 14.30 & 12.30 & 16.30 & 31.75 & 9.80 \\ \hline Tip & 2.34 & 1.89 & 0.00 & 4.29 & 2.46 & 1.50 & 2.98 & 1.96 \end{tabular}
The regression equation is $\hat{y}=$ $\square$ $+$ $\square$ $x$ . (Round the $y$ -intercept to two decimal places as needed. Round the slope to four decimal places as needed.)

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Problem 991

Find the regression equation, letting the first variable be the predictor ( x ) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 44 years. Is the result within 5 years of the actual Best Actor winner, whose age was 45 years? Use a significance level of 0.05 . \begin{tabular}{cllllllllllll} \hline Best Actress & 27 & 32 & 28 & 58 & 30 & 34 & 47 & 30 & 62 & 22 & 44 & 56 \\ Best Actor & 44 & 37 & 37 & 47 & 48 & 46 & 62 & 49 & 37 & 55 & 45 & 33 \\ \hline \end{tabular}
Find the equation of the regression line. $\hat{\mathrm{y}}=\square+(\square) \mathrm{x}$ (Round the $y$ -intercept to one decimal place as needed. Round the slope to three decimal places as needed.)

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Problem 992

A businesswoman is considering whether to open a coffee shop in a local shopping center. Before making this decision, she wants to know how much money people spend per week at coffee shops in that area. She took a random sample of 26 customers from the area who visit coffee shops and asked them to record the amount of money (in dollars) they would spend during the next week at coffee shops. At the end of the week, she obtained the following data (in dollars) from these 26 customers: \begin{tabular}{lllllllll} 16.91 & 38.63 & 15.22 & 14.34 & 5.05 & 63.69 & 10.28 & 13.21 & 32.20 \\ 36.04 & 16.29 & 65.93 & 10.27 & 37.13 & 3.15 & 6.81 & 34.67 & 6.47 \\ 36.25 & 27.66 & 38.71 & 13.17 & 9.64 & 9.39 & 1.30 & 5.16 & \end{tabular}
Assume that the distribution of weekly expenditures at coffee shops by all customers who visit coffee shops in this area is approximately normal.
Round your answers to cents. a. What is the point estimate of the corresponding population mean? $\bar{x}=\$$ i $\square$ b. Make a 95\% confidence interval for the average amount of money spent per week at coffee shops by all customers who visit coffee shops in this area. \$ i 1 ! to \$ i

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Problem 993

For a confidence level of $98 \%$ with a sample size of 21 , find the critical $t$ -value (also known as the $t$ -score). $\square$ (round to 3 decimal places)

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Problem 994

The records of a casualty insurance company show that, in the past, its clients have had a mean of 1.7 auto accidents per day with a variance of 0.0025 . The actuaries of the company claim that the variance of the number of accidents per day is no longer equal to 0.0025 . Suppose that we want to carry out a hypothesis.test to see if there is support for the actuaries' claim. State the null hypothesis $H_{0}$ and the alternative hypothesis $H_{1}$ that we would use for this test. $\begin{array}{l} H_{0}: \square \\ H_{1}: \square \end{array}$

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Problem 995

1. Below is a hypothesis test. Label the different parts of the test in the boxes.
A hospital director is told that $47 \%$ of the treated patients are uninsured. The director wants to test the claim that the percentage of uninsured patients is over the expected percentage. A sample of 400 patients is found that 200 were uninsured. At the 0.02 level, is there enough evidence to support the director's claim? $\begin{array}{l} H_{o}: p \leq 0.47 \\ H_{a}: p>0.47 \end{array}$ $\square$

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Problem 996

Find the critical value(s) and rejection region(s) for the type of z-test with level of significance $\alpha$ . Include a graph with your Right-tailed test, $\alpha=0.05$
The critical value(s) is/are $z=1.645$ . (Round to two decimal places as needed. Use a comma to separate answers as needed.) Select the correct choice below and, if necessary, fill in the answer box to complete your choice. (Round to two decimal places as needed.) A. The rejection region is $z<\square$ . B. The rejection region is $z>1.645$ . C. The rejection regions are $z<\square$ and $z>\square$ .
Choose the correct graph of the rejection region below.
$B$ . c.

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Problem 997

Hypothesis test for the population mean: $t$ test using the critical value...
An electronics manufacturing process has historically had a mean completion time of 70 minutes. It is clured that, due to improvements in the process, the mean completion time, $\mu$ , is now less than 70 minutes. A random sample of 22 completion times using the new process is taken. The sample has a mean completion time of 67 minutes, with a standard deviation of 12 minutes.
Assume that completion times using the new process are approximately normally distributed. At the 0.05 level of significance, can it be concluded that the pepulation mean completion time using the new process is less than 70 minutes?
Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. (If necessary, consult a list of formulas.) (a) State the null hypothesis $H_{0}$ and the alternative hypothesis $H_{1}$ . $\begin{array}{l} H_{0}: \square \\ H_{1}: \square \end{array}$ $\Rightarrow H_{1}$ (b) Determine the type of test statistic to use. (Choose one) (c) Find the value of the test statistic. (Round to three or more decimal places.) $\square$ (d) Find the critical value. (Round to three or more decimal places.) $\square$ (e) Can it be concluded that the mean completion time using the new process is less than 70 minutes? Yes No

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Problem 998

The records show that the lifetimes of electric bulbs manufactured in the past by BIG Corporation have a mean of 9790 hours and a standard deviation of 124 . The corporation claims that the current standard deviation, $\sigma$ , is less than 124 following some adjustments in its production unit. A random sample of 27 bulbs from the current production lot is examined by the corporation. The sample has a mean lifetime of 9795 hours, with a standard deviation of 90 . Assume that the lifetimes of the recently manufactured bulbs are approximately normally distributed, Is there enough evidence to conclude, at the 0.10 level of significance, that the corporation's claim is valid?
Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. (If necessary, consult a list of formulas.) (a) State the null hypothesis $H_{0}$ and the alternative hypothesis $H_{1}$ . $\begin{array}{l} H_{0}: \square \\ H_{1}: \square \end{array}$ (b) Determine the type of test statistic to use. (Choose one) (c) Find the value of the test statistic. (Round to three or more decimal places.) $\square$ (d) Find the critical value. (Round to three or more decimal places.) $\square$ (e) Can we support the claim that the current standard deviation of lifetimes of electric bulbs manufactured by the corporation is less than 124 ? Yes No

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Problem 999

Are freshmen psychology majors just as likely to change their major before they graduate compared to freshmen business majors? 428 of the 671 freshmen psychology majors from a recent study changed their major before they graduated and 426 of the 643 freshmen business majors changed their major before they graduated. What can be concluded at the $\alpha=0.05$ level of significance?
For this study, we should use Select an answer a. The null and alternative hypotheses would be: $H_{0}$ : Select an answer Select an answer Select an answer $H_{1}$ : Select an answer Select an answer Select an answer b. The test statistic ? $=$ $\square$ (please show your answer to 3 decimal places.) c. The $p$ -value $=$ $\square$ (Please show your answer to 4 decimal places.) d. The $p$ -value is ? $\alpha$ e. Based on this, we should Select an answer the null hypothesis. f. Thus, the final conclusion is that ... The results are statistically significant at $\alpha=0.05$ , so there is sufficient evidence to conclude that the population proportion of freshmen psychology majors who change their major is different from the population proportion of freshmen business majors who change their major. The results are statistically significant at $\alpha=0.05$ , so there is sufficient evidence to conclude that the proportion of the 671 freshmen psychology majors who changed their major is different from the proportion of the 643 freshmen business majors who change their major. 0 The results are statistically insignificant at $\alpha=0.05$ , so there is insufficient evidence to conclude that the population proportion of freshmen psychology majors who change their major is different from the population proportion of freshmen business majors who change their major. The results are statistically insignificant at $\alpha=0.05$ , so there is statistically significant evidence to conclude that the population proportion of freshmen psychology majors who change their major is the same as the population proportion of freshmen business majors who change their major.

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Problem 1000

Are freshmen psychology majors less likely to change their major before they graduate compared to freshmen business majors? 339 of the 636 freshmen psychology majors from a recent study changed their major before they graduated and 426 of the 723 freshmen business majors changed their major before they graduated. What can be concluded at the $\alpha=0.01$ level of significance? If the calculator asks, be sure to use the "Pooled" data option.
For this study, we should use Select an answer a. The null and alternative hypotheses would be: $H_{0}$ : Select an answer Select an answer Select an answer (6) (please enter a decimal) $H_{1}$ : Select an answer Select an answer Select an answer (Please enter a decimal) b. The test statistic ? $\mathbf{0}=$ $\square$ (please show your answer to 3 decimal places.) c. The p -value $=$ $\square$ (Please show your answer to 4 decimal places.) d. The $p$ -value is $\square$ $\alpha$ e. Based on this, we should Select an answer the null hypothesis. f. Thus, the final conclusion is that ... The results are statistically significant at $\alpha=0.01$ , so there is sufficient evidence to conclude that the population proportion of freshmen psychology majors who change their major is less than the population proportion of freshmen business majors who change their major. The results are statistically insignificant at $\alpha=0.01$ , so there is insufficient evidence to conclude that the population proportion of freshmen psychology majors who change their major is less than the population proportion of freshmen business majors who change their major. The results are statistically significant at $\alpha=0.01$ , so there is sufficient evidence to conclude that the proportion of the 636 freshmen psychology majors who changed their major is less than the proportion of the 723 freshmen business majors who change their major. The results are statistically insignificant at $\alpha=0.01$ , so there is statistically significant evidence to conclude that the population proportion of freshmen psychology majors who change their major is the same as the population proportion of freshmen business majors who change their major.

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Statistical Inference

Problem 901

Problem 902

Problem 903

Valerie's team of 30 rated her as "outstanding" at 83%83\%83%. Why might this result be biased? Choose 1 answer: A, B, C, or D.

Problem 904

Problem 905

Problem 906

Problem 907

Problem 908

Problem 909

Problem 910

Problem 911

Problem 912

Problem 913

From a random sample of 80 women, 48 say they have been sexually harassed. From another random sample of 65 men, 13 say they have been sexually harassed. Construct a 99%99 \%99% confidence interval for the difference between the proportions of women and men who say they have been sexually harassed.

Problem 914

Problem 915

Problem 916

Problem 917

Problem 918

Problem 919

Problem 920

Problem 921

Problem 922

Problem 923

Problem 924

Problem 925

Problem 926

Problem 927

Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places) \begin{tabular}{|c|c|} \hlinexxx & yyy \\ \hline 3 & 27.61 \\ \hline 4 & 29.88 \\ \hline 5 & 29.95 \\ \hline 6 & 31.32 \\ \hline 7 & 34.89 \\ \hline 8 & 35.06 \\ \hline \end{tabular}

Problem 928

Select the appropriate word or phrase to complete the sentence.The number of degrees of freedom for the Student's ttt-test of a population mean is always 1 less than the (Choose one) ∇\nabla∇.

Problem 929

Problem 930

Problem 931

Problem 932

Problem 933

Problem 934

Problem 935

Problem 936

Problem 937

Problem 938

We poll 450 people and find that 40%40 \%40% favor Candidate S. In order to estimate with 90%90 \%90% confidence the percent of ALL voters would vote for Candidate S, we should use: 2-SampZInt 2-PropZInt TInterval 1-PropZInt 2-SampTInt ZInterval

Problem 939

Problem 940

Answer the following True or False: A researcher hypothesizes that the average student spends less than 20%20 \%20% of their total study time reading the textbook. The appropriate hypothesis test is a left tailed test for a population mean. false true

Problem 941

Problem 942

Problem 943

Problem 944

Problem 945

Problem 946

Problem 947

Problem 948

Problem 949

Problem 950

Suppose that shoe sizes of American women have a bell-shaped distribution with a mean of 8.19 and a standard deviation of 1.49 . Using the empirical rule, what percentage of American women have shoe sizes that are no more than 11.17 ? Please do not round your answer.

Problem 951

Problem 952

Problem 953

Problem 954

Problem 955

Problem 956

Problem 957

Problem 958

In Oak City, predict how many adults get news from newspapers based on a sample of 50,000. Round to the nearest whole number.

Problem 959

Use the Grubbs test to check if 0.11890.11890.1189 is an outlier in the data set 0.1123,0.1087,0.1139,0.1112,0.11890.1123, 0.1087, 0.1139, 0.1112, 0.11890.1123,0.1087,0.1139,0.1112,0.1189 at 95%95\%95% confidence. Show your calculations.

Problem 960

Problem 961

Problem 962

Problem 963

Problem 964

Problem 965

Problem 966

Problem 967

Problem 968

Problem 969

Problem 970

Valerie's team of 30 rated her as "outstanding" at $83\%$ . Why might this result be biased? Choose 1 answer: A, B, C, or D.

From a random sample of 80 women, 48 say they have been sexually harassed. From another random sample of 65 men, 13 say they have been sexually harassed. Construct a $99 \%$ confidence interval for the difference between the proportions of women and men who say they have been sexually harassed.

Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places) \begin{tabular}{|c|c|} \hline $x$ & $y$ \\ \hline 3 & 27.61 \\ \hline 4 & 29.88 \\ \hline 5 & 29.95 \\ \hline 6 & 31.32 \\ \hline 7 & 34.89 \\ \hline 8 & 35.06 \\ \hline \end{tabular}

Select the appropriate word or phrase to complete the sentence.
The number of degrees of freedom for the Student's $t$ -test of a population mean is always 1 less than the (Choose one) $\nabla$ .

We poll 450 people and find that $40 \%$ favor Candidate S. In order to estimate with $90 \%$ confidence the percent of ALL voters would vote for Candidate S, we should use: 2-SampZInt 2-PropZInt TInterval 1-PropZInt 2-SampTInt ZInterval

Answer the following True or False: A researcher hypothesizes that the average student spends less than $20 \%$ of their total study time reading the textbook. The appropriate hypothesis test is a left tailed test for a population mean. false true

Use the Grubbs test to check if $0.1189$ is an outlier in the data set $0.1123, 0.1087, 0.1139, 0.1112, 0.1189$ at $95\%$ confidence. Show your calculations.