Statistical Inference

Problem 1001

n/Student/PlayerHomework.aspx?homeworkld=680302994\&questionld=2\&flushed=false\&cld=7951706\¢erwin=yes g and Applications Tyler Jernigan 0.3 HW - Hypothesis Tests for a Question 1, 10.3.1 HW Score: $45.9 \%, 5.97$ of 13 points lean Part 1 of 3 Points: 0.67 of 1
Complete parts (a) through (c) below. (a) Determine the critical value(s) for a right-tailed test of a population mean at the $\alpha=0.10$ level of significance with 15 degrees of freedom. (b) Determine the critical value(s) for a left-tailed test of a population mean at the $\alpha=0.01$ level of significance based on a sample size of $n=20$ . (c) Determine the critical value(s) for a two-tailed test of a population mean at the $\alpha=0.05$ level of significance based on a sample size of $n=12$ .
Click here to view the t-Distribution Area in Right Tail.

See Solution

Problem 1002

A1 . M2 - TC - Lesson 18 PRACTICE
On a track team, 4 athletes compare their fastest times in the 100 -meter race and 200 -meter race. A table of their fastest times is shown. The athletes wonder whether a faster 100 -meter time is associated with a faster 200 -meter time. \begin{tabular}{c|c|c} Athlete & \begin{tabular}{c} Fastest Time \\ 100-Meter Race \\ (seconds) \end{tabular} & \begin{tabular}{c} Fastest Time \\ 200-Meter Race \\ (seconds) \end{tabular} \\ \hline A & 12.95 & 26.68 \\ \hline B & 13.81 & 29.48 \\ \hline C & 14.66 & 28.11 \\ \hline D & 14.88 & 30.93 \\ \hline \end{tabular}

See Solution

Problem 1003

A researcher wants to know if the clothes a woman wears is a factor in her GPA. The table below shows data that was collected from a survey. \begin{tabular}{|c|c|c|c|} \hline Shorts & Dress & Jeans & Skirt \\ \hline 2.4 & 2.7 & 2.9 & 2.9 \\ \hline 2.3 & 2.3 & 2.8 & 3.4 \\ \hline 4 & 2.2 & 3.6 & 4 \\ \hline 3.1 & 3.5 & 2.9 & 3.9 \\ \hline 3.3 & 3.2 & 3.2 & 2.5 \\ \hline 2.1 & 2.4 & 4 & 3.5 \\ \hline 3.1 & 3.4 & 2.7 & 3.7 \\ \hline 3 & 2.1 & 3.5 & \\ \hline 3.2 & & & \\ \hline \end{tabular}
Assume that all distributions are normal, the four population standard deviations are all the same, and the data was collected independently and randomly. Use a level of significance of $\alpha=0.1$ . $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}=\mu_{4}$ $H_{1}$ : At least two of the means differ from each other.
1. For this study, we should use Select an answer
2. The test-statistic for this data $=$ $\square$ (Please show your atiswer to 3 decimal places.)
3. The $p$ -value for this sample $=$ $\square$ (Please show your answer to 4 decimal places.)
4. The $p$ -value is Select an answer - $a$
5. Base on this, we should Select an answer
6. As such, the final conclusion is that... There is sufficient evidence to support the claim that the clothes a woman wears is a factor in GPA. There is insufficient evidence to support the claim that the clothes a woman wears is a factor in GPA.

See Solution

Problem 1004

Three students, Linda, Tuan, and Javier, are given laboratory rats for a nutritional experiment. Each rat's weight is recorded in grams. Linda feeds her rats Formula A, Tuan feeds his rats Formula B, and Javier feeds his rats Formula C. At the end of a specified time period, each rat is weighed again, and the net gain in grams is recorded. Using a significance level of 0.05 , test the hypothesis that the three formulas produce the same mean weight gain. $H_{0}: \mu_{1}=\mu_{2}=\mu_{3}$ $\mathrm{H}_{\mathrm{a}}$ : At least two of the means differ from each other \begin{tabular}{|c|c|c|} \hline Forumla A & Forumla B & Forumla C \\ \hline 947.1 & 45.1 & 51.4 \\ \hline 44 & 39.9 & 58 \\ \hline 939 & 35 & 52 \\ \hline 52.9 & 34.1 & 44.3 \\ \hline 37.3 & 60.6 & 48.8 \\ \hline 55.7 & 57 & 47.5 \\ \hline 52 & 20.9 & 42.3 \\ \hline 57.7 & 18.3 & 40.6 \\ \hline 1261.4 & 41.3 & 50.6 \\ \hline \end{tabular}
Run a one-factor ANOVA with $\alpha=0.05$ . Report the F -ratio to 4 decimal places and the p -value to 4 decimal places. $F=$ p-value = $\square$ Based on the $p$ -value, what is the conclusion Reject the null hypothesis: at least one of the group means is different Fail to reject the null hypothesis: not sufficient evidence to suggest the group means are different

See Solution

Problem 1005

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? $\begin{array}{l} H_{o}: p \leq 0.47 \\ H_{a}: p>0.47 \end{array}$ $Z=\frac{\hat{p}-p}{\sqrt{\frac{p(1-p)}{n}}}=\frac{0.5-0.47}{\sqrt{\frac{0.47(1-0.47)}{400}}}=\frac{0.03}{\sqrt{\frac{0.47(0.53)}{400}}}=\frac{0.03}{\sqrt{\frac{0.2491}{400}}}=\frac{0.03}{\sqrt{0.00062275}}=\frac{0.03}{0.02495}=1.20$

See Solution

Problem 1006

Women stereotypically talk more than men do and researchers wondered how much more. Suppose a study attempted to determine the difference in the mean number of words spoken by men or women per day. The results of the study are summarized in the table. \begin{tabular}{cccccc} Group & \begin{tabular}{c} Population \\ mean \end{tabular} & \begin{tabular}{c} Sample \\ size \end{tabular} & \begin{tabular}{c} Sample \\ mean \end{tabular} & \begin{tabular}{c} Sample standard \\ deviation \end{tabular} & \begin{tabular}{c} Standard error \\ estimate \end{tabular} \\ \hline women & $\mu_{\mathrm{w}}$ (unknown) & $n_{\mathrm{w}}=27$ & $\bar{x}_{\mathrm{w}}=16496$ & $s_{\mathrm{w}}=7914$ & $\mathrm{SE}_{\mathrm{w}}=1523$ \\ men & $\mu_{\mathrm{m}}$ (unknown) & $n_{\mathrm{m}}=20$ & $\bar{x}_{\mathrm{m}}=12867$ & $s_{\mathrm{m}}=8230$ & $\mathrm{SE}_{\mathrm{m}}=1840$ \end{tabular} $\mathrm{df}=40.1700$
Assume the conditions are satisfied for a two-sample $t$ -confidence interval. First, determine the positive critical value, $t$ , for a $99 \%$ confidence interval to estimate how many more words women speak each day on average compared to men, $\mu_{\mathrm{w}}-\mu_{\mathrm{m}}$ .
Give your answer precise to at least three decimal places. $t=2.861$

See Solution

Problem 1007

Mara Stratton 12/03/24 6:28 PM Question 6, 10.3.21-T HW Score: $47.62 \%, 20$ of 42 points lomework Part 4 of 5 Points: 0 of 2 Save
The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 86.8 seconds. A manager devises a new drive-through system that he believes will decrease wait time. As a test, he initiates the new system at his restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. \begin{tabular}{|c|c|} \hline 105.8 & 82.9 \\ 66.1 & 96.3 \\ 59.6 & 85.3 \\ 76.2 & 72.3 \\ 65.2 & 80.3 \\ \hline \end{tabular}
Click the icon to view the table of correlation coefficient critical values. (b) Is the new system effective? Conduct a hypothesis test using the P -value approach and a level of significance of $\alpha=0.01$ .
First determine the appropriate hypotheses. $\begin{array}{l} H_{0}: \mu=86.8 \\ H_{1}: \mu=86.8 \end{array}$
Find the test statistic. $t_{0}=-1.73$ (Round to two decimal places as needed.) Find the P -value. The $P$ -value is $\square$ . (Round to three decimal places as needed.)
Time (sec) 3 xample Get more help - Clear all Final check

See Solution

Problem 1008

Part 5 of 6 Points: 0 of 1
A simple random sample of size $n$ is drawn. The sample mean, $\bar{x}$ , is found to be 17.9 , and the sample standard deviation, $s$ , is found to be 4.2 . (a) Construct a $95 \%$ confidence interval about $\mu$ if the sample size, n , is 34 .
Lower bound: 16.43 ; Upper bound: 19.37 (Use ascending order. Round to two decimal places as needed.) (b) Construct a $95 \%$ confidence interval about $\mu$ if the sample size, n , is 61.
Lower bound: 16.83 ; Upper bound: 18.98 (Use ascending order. Round to two decimal places as needed.) How does increasing the sample size affect the margin of error, E? A. The margin of error increases. B. The margin of error decreases. C. The margin of error does not change. (c) Construct a 99\% confidence interval about $\mu$ if the sample size, n , is 34 .
Lower bound: 15.93; Upper bound: 19.87 (Use ascending order. Round to two decimal places as needed.) Compare the results to those obtained in part (a). How does increasing the level of confidence affect the size of the margin of error, E? A. The margin of error decreases. B. The margin of error does not change. C. The marnin of error increases

See Solution

Problem 1009

Section 9.2 Homework Question 9, 9.2.28 HW Score: 47.14\%, 15.56 of 33 points Part 3 of 4 Points: 0 of 1 Save
A nutritionist wants to determine how much time nationally people spend eating and drinking. Suppose for a random sample of 951 people age 15 or older, the mean amount of time spent eating or drinking per day is 1.32 hours with a standard deviation of 0.52 hour. Complete parts (a) through (d) below.
Click the icon to view the table of critical t-values. that both tails are accounted for in the confidence interval. D. Since the distribution of time spent eating and drinking each day is highly skewed right, a large sample size is needed to minimize the margin of error to ensure only the peak of the sampling distribution is captured in the confidence interval. (b) There are more than 200 million people nationally age 15 or older. Explain why this, along with the fact that the data were obtained using a random sample, satisfies the requirements for constructing a confidence interval. A. The sample size is greater than $10 \%$ of the population. B. The sample size is greater than $5 \%$ of the population. C. The sample size is less than $5 \%$ of the population. D. The sample size is less than $10 \%$ of the population. (c) Determine and interpret a 95\% confidence interval for the mean amount of time Americans age 15 or older spend eating and drinking each day.
Select the correct choice below and fill in the answer boxes, if applicable, in your choice. (Type integers or decimals rounded to three decimal places as needed. Use ascending order.) A. The nutritionist is $95 \%$ confident that the amount of time spent eating or drinking per day for any individual is between $\square$ and B. The nutritionist is $95 \%$ confident that the mean amount of time spent eating or drinking per day is between $\square$ and $\square$ hours. C. There is a $95 \%$ probability that the mean amount of time spent eating or drinking per day is between $\square$ and $\square$ hours.

See Solution

Problem 1010

C10 Q10 V3: The Excel file STATISTICSSTUDENTSSURVEYFORR contains the column ENDPULSEMIN (a numerical variable that measures student pulses after completing an online survey) and the column BEFPULSEMIN (a numerical variable that measures student pulses before completing an online survey). For education purposes, consider this dataset to be a sample of size 60 taken from a much larger population for statistics students. Consider the paired differences $d=$ ENDPULSEMIN BEFPULSEMIN. Calculate a $90 \%$ confidence interval for the mean of the population paired differences. Choose the most correct (closest) answer. a. Your confidence interval is $(0.4746613,1.5253387)$ and there is significant evidence that, on average, the two pulse rate measurements give different results. b. Your confidence interval is ( $0.5612735,1.4387265$ ) and there is no significant evidence that, on average, the two pulse rate measurements give different results, on average. c. Your confidence interval is ( $0.4746613,1.5253387$ ) and there is no significant evidence that, on average, the two pulse rate measurements give different results. d. Your confidence interval is $(0.5612735,1.4387265)$ and there is significant evidence that, on average, the two pulse rate measurements give different results.

See Solution

Problem 1011

C13 Q2 V3 The Excel file STATISTICSSTUDENTSSURVEYFORR contains the column MOTHDEGREE (a categorical variable that indicates the degree obtained (or being obtained) by a student's mother (GraduateProfessional, HighSchool, Undergraduate) and the column BAORBS (a categorical variable that indicates whether a student is pursuing a BA or a BS. We consider, somewhat artificially, the statistics 151 student data in the STATISTICSSTUDENTSSURVEYFORR file to be a random sample from a much larger hypothetical population of Canadian students. Using a level of significance of $5 \%$ , you perform a test of independence to determine if mother's final degree and student bachelorá s degree are independent. Choose the most correct (closest) answer below. a. A Chi-square test of independence requires numerical variables and you cannot do this problem. b. Your pvalue is 0.449 , and you reject your null hypothesis. c. Your pvalue is 0.2245 , and you fail to reject your null hypothesis. d. Your pvalue is 0.449 , and you fail to reject your null hypothesis.

See Solution

Problem 1012

Find the best predicted value of $y$ given that $x=5$ for 6 pairs of data that yield $r=0.444, \bar{y}=18.3$ and the regression equation $y=2+5 x$ . State the critical level.

See Solution

Problem 1013

The least squares method minimizes which of the following? All of the above SST SSE SSR

See Solution

Problem 1014

Blood pressure: A blood pressure measurement consists of two numbers: the systolic pressure, which is the pressure taken when the heart is contracting, and the diastolic pressure, which is the minimum pressuretaker beginning of the heartbeat. Blood pressures were measured, in millimeters of mercury ( mmHg ), for a sample The following table presents the results. Use a TI-84 calculator to answer the following. \begin{tabular}{cccc} \hline Systolic & Diastolic & Systolic & Diastolic \\ \hline 112 & 75 & 157 & 103 \\ 107 & 71 & 154 & 94 \\ 110 & 74 & 134 & 87 \\ 108 & 69 & 115 & 83 \\ 105 & 66 & 113 & 77 \\ \hline \end{tabular}
Based on results published in the Journal of Human Hypertension Send data to Excel
Part: $0 / 4$
Part 1 of 4 Compute the least-squares regression line for predicting the diastolic pressure from the systolic pressure. $R$ slope and $y$ -intercept to at least four decimal places.
Reqression line equation: $\hat{y}=$ $\square$

See Solution

Problem 1015

Given data on shopping habits by location, answer these:
A) Is living location "independent" or "dependent" of shopping choice?
B) Are observed values "same" or "different" from expected if dependent?
C) Expected urban shoppers at supermarket if independent? (Round to nearest tenth)
D) What is the $p$ -value for independence test? (Round to nearest tenth)
E) Is there evidence of a relationship between living location and shopping choice? "yes" or "no"

See Solution

Problem 1016

Tina's survey of 600 students shows $53\%$ exercise over 30 mins daily. Why is this misleading? Choose one: outlier, small sample, biased sample, calculation error.

See Solution

Problem 1017

If more driver's ed hours lead to fewer accidents, this indicates a $a(n)$ : A. negative correlation B. casual relationship C. ambiguous correlation D. positive correlation.

See Solution

Problem 1018

Click here to view the weight and gas mileage data. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. $\hat{y}=-0.00866 x+(49.4)$ (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and $y$ -intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. A weightless car will get $\square$ miles per gallon, on average. It is not appropriate to interpret the slope. B. For every pound added to the weight of the car, gas mileage in the city will decrease by $\square$ mile(s) per gallon, on average. It is not appropriate to interpret the $y$ -intercept. C. For every pound added to the weight of the car, gas mileage in the city will decrease by $\square$ mile(s) per gallon, on average. A weightless car will get $\square$ miles per gallon, on average. D. It is not appropriate to interpret the slope or the $y$ -intercept.

See Solution

Problem 1019

Testing whether Story Spoilers Spoil Stories A story spoiler gives away the ending early. Does having a story spoiled in this way diminish suspense and hurt enjoyment? A study ${ }^{1}$ investigated this question. For twelve different short stories, the study's authors created a second version in which a spoiler paragraph at the beginning discussed the story and revealed the outcome. Each version of the twelve stories was read by at least 30 people and rated on a 1 to 10 scale to create an overall rating for the story, with higher ratings indicating greater enjoyment of the story. The ratings are given in Table 1 and stored in StorySpoilers. Stories 1 to 4 were ironic twist stories, stories 5 to 8 were mysteries, and stories 9 to 12 were literary stories. Test to see if there is a difference in mean overall enjoyment rating based on whether or not there - is a spoiler. \begin{tabular}{llllllllllllll} \hline Story & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \begin{tabular}{l} With \\ spoiler \end{tabular} & 4.7 & 5.1 & 7.9 & 7.0 & 7.1 & 7.2 & 7.1 & 7.2 & 4.8 & 5.2 & 4.6 & 6.7 \\ \begin{tabular}{l} Original \end{tabular} & 3.8 & 4.9 & 7.4 & 7.1 & 6.2 & 6.1 & 6.7 & 7.0 & 4.3 & 5.0 & 4.1 & 6.1 \\ \hline \end{tabular}
Table 1 Enjoyment ratings for stories with and without spoilers
Click here for the dataset associated with this question. ${ }^{1}$ Leavitt, J. and Christenfeld, N., "Story Spoilers Don't Spoil Stories," Psychological Science, published OnlineFirst, August 12, 2011.
Part 1 - Your answer is partially correct.
Give the test statistic and the $p$ -value. Round your answer for the test statistic to two decimal places and your answer for the $p$ -value to four decimal places. test statistic $=$ $\square$ 4.92 $p$ -value $=$ $\square$ $!$

See Solution

Problem 1020

Select the appropriate word or pprase to complete the sentence.
The $\square$ hypothesis states that a parameter is equal to a certain value while the (Choose one) $\square$ hypothesis states that the parameter differs from this value.

See Solution

Problem 1021

New Tab Como alterar o ico... Who We Are | Mas... http://www.bit.ly/C... traducao Gmail YouTube Maps All Bookmar Mara Stratton 12/03/24 9:11 PM n 11.1 Homework Question 3, 11.1.17-T HW Score: 50\%, 5 of 10 points Save Part 5 of 6 Points: 0 of 4
In randomized, double-blind clinical trials of a new vaccine, rats were randomly divided into two groups. Subjects in group 1 received the new vaccine while subjects in group 2 received a control vaccine. After the second dose, 113 of 748 subjects in the experimental group (group 1) experienced fever as a side effect. After the second dose, 70 of 629 of the subjects in the control group (group 2) experienced fever as a side effect. Does the evidence suggest that a higher proportion of subjects in group 1 experienced fever as a side effect than subjects in group 2 at the $\alpha=0.10$ level of significance? C. The samples are independent. D. The samples are dependent. E. The sample size is less than $5 \%$ of the population size for each sample. F. The data come from a population that is normally distributed.
Determine the null and alternative hypotheses. $\begin{array}{l} H_{0}: p_{1}=p_{2} \\ H_{1}: p_{1}>p_{2} \end{array}$
Find the test statistic for this hypothesis test. 2.17 (Round to two decimal places as needed.)
Determine the P-value for this hypothesis test. 0.015 (Round to three decimal places as needed.)
Interpret the P -value. If the population proportions are $\square$ one would expect a sample difference proportion $\square$ the one observed in about $\square$ out of 1000 repetitions of this experiment. (Round to the nearest integer as needed.) an example Get more help - Clear all Check an:

See Solution

Problem 1022

Teens, Social Media and Technology A new Pew Research Center survey of 1316 American teenagers ages 13 to 17 finds TikTok has rocketed in popularity since its North American debut several years ago $Æ$ and now is a top social media platform for teens among the platforms covered in this survey. Some $67 \%$ of teens say they use TikTok, with $16 \%$ of all teens saying they use it almost constantly. Meanwhile, the share of teens who say they use Facebook, a dominant social media platform among teens in the Center's 2014-15 survey $巴$ , has plummeted from $71 \%$ then to $32 \%$ today. Below is a graph depicting the percent of usage of various Social Media by teens in the survey. This poll has a margin of error of $+/-3.2 \%$ .
About one-In-flive teens visit or use YouTube 'almost constantly' \% of U.S. teens who say they -- 8 Fill in the Blank 10 points Calculate the confidence interval for those teens who 'ever use' TikTok. type your answer... \% to type your answer... 9 Fill in the Blank 10 points
Calculate the confidence interval for those teens who almost constantly visit or use TikTok. type your answer... \% to type your answer... \% 10 'Essay 10 points
Using the interval calculated directly above, write a $95 \%$ confidence statement regarding the specific social media use. Edit View Insert Format Tools Table 12pt $\vee$ Paragraph
Note Teens refer to those ages 13 to 17. Those who did not give an answer or gave other responses are not shown Source: Survey conducted April 14-May 4, 2022 Teens, Social Media and Technology $2022^{-}$ PEW RESEARCH CENTER

See Solution

Problem 1023

A manufacturer of women's clothing is interested to know if age is a factor in whether women would buy a particular garment depending on its quality. A researcher samples 3 age groups and each woman is asked to rate the garment as excellent, average or poor as shown in the table below: \begin{tabular}{|c|c|c|c|c|} \cline { 2 - 5 } \multicolumn{2}{|c|}{} & \multicolumn{3}{c|}{ Age group } \\ \cline { 2 - 5 } & Excellent & $15-20$ & $21-30$ & $31-60$ \\ \hline 20 & 40 & 47 & 46 \\ \hline & Average & 51 & 74 & 57 \\ \hline & Poor & 29 & 19 & 37 \\ \hline \end{tabular}
Test the bypothesis, at $5 \%$ level of significance, that rating is not related to age group. [25]

See Solution

Problem 1024

X Do Homework - Homework 1B X P Do Homework - Homework 6B X Desmos | Scientific Calculator X CS Testing Center | Chattanooga x + on.com/Student/PlayerHomework.aspx?homeworkId=678248859&questionid=7&flushed=false&cid=7910058&back=https://mylab.pearson.com/Student/DoAssignments.aspx?wl_access_status=opted-in&&wl_access_date=2024-10-14T13:... oductory Statistics 6B (4.2-4.3) K < Question 16, 4.3.X1 Part 1 of 3 K'lyah Harris 12/03/ HW Score: 82.5%, 13.2 of 16 points O Points: 0 of 1 The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r = -0.969. The least-squares regression line treating explanatory variable and miles per gallon as the response variable is y = -0.0060x + 41.3516. Complete parts (a) through (c) below. Click the icon to view the data table. (a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? The proportion of the variability in miles per gallon explained by the relation between freight of the car and miles per gallon is %. (Round to one decimal place as needed.)

See Solution

Problem 1025

is asked to rate the garment as excellent, average or poor as shown in the table \begin{tabular}{|c|c|c|c|c|} \hline & & \multicolumn{3}{|c|}{Age group} \\ \hline & & 15-20 & 21-30 & 31-60 \\ \hline \multirow{3}{*}{ $\frac{8}{2}$ } & Excellent & 40 & 47 & 46 \\ \hline & Average & 51 & 74 & 57 \\ \hline & Poor & 29 & 19 & 37 \\ \hline \end{tabular} nthesis, at $5 \%$ level of significance, that rating is not related to age group.

See Solution

Problem 1026

A significant F-ratio is obtained in an ANOVA when At least two means differ significantly. All means differ significantly The sample mean differs from the population mean. The sample variance differs from the population variance.

See Solution

Problem 1027

Calculate the correlation coefficient for the following data. Round your answer to the nearest thousandth. \begin{tabular}{|c|c|} \hline $x$ & $y$ \\ \hline 6 & 63.7 \\ \hline 7 & 88.7 \\ \hline 9 & 60.6 \\ \hline 11 & 20.6 \\ \hline 13 & 80.8 \\ \hline 16 & 57.7 \\ \hline 19 & 18.4 \\ \hline \end{tabular}
Copy Data
Answer

See Solution

Problem 1028

Homework 7.2 Question 3 of 7 (1 point) I Question Attempt: 2 of Unlimited Salma $\checkmark 1$ $\checkmark 2$ $=3$ 4 5 6 7 Español
Freshmen GPAs First-semester GPAs for a random selection of freshmen at a large university are shown below. Estimate the true mean GPA of the freshman class with $97 \%$ confidence. Assume $\sigma=0.62$ . Use a graphing calculator and round the answers to two decimal places. Assume the population is normally distributed. \begin{tabular}{ll|l|l|l|l|l|l|l} 2.8 & 1.9 & 4 & 2.2 & 2.8 & 2.9 & 2.1 & 3 & 3.8 \\ 2.7 \\ 2.1 & 2.4 & 2 & 1.9 & 2.5 & 2 & 2.8 & 3.2 & 3 \\ 3.1 & 2.7 & 3 & 3.4 & 3.5 & 3.8 & 3.9 & 2.7 & \\ 3.8 \end{tabular} Send data to Excel $2.66^{\otimes}<\mu<3.18$
Try one last time Save For Later Submit Assignment

See Solution

Problem 1029

https://www-awy.aleks.com/alekscgi/x/Isl.exe/1o_u-IgNslkasNW8D8A9PVVfaYzvAnKbEZqvmttIlkfkbx0fBm18LItV2MuhXGp6DIxVkZL9gT1iQIckInala8TfY0BOXp5... Homework 7.2 Question 4 of 7 (1 point) I Question Attempt: 1 of Unlimited Salma $\checkmark 1$ $\checkmark 2$ $\times 3$ 4 5 6 7 Español
Number of Farms A random sample of the number of farms (in thousands) in various states follows. Estimate the mean number of farms per state with $99 \%$ confidence. Assume $\sigma=31$ . Round intermediate and final answers to one decimal place. Assume the population is normally distributed. \begin{tabular}{lllllllclll} 48 & 79 & 44 & 49 & 3 & 90 & 80 & 9 & 57 & 8 & 4 \\ 64 & 33 & 54 & 95 & 47 & 50 & 40 & 109 & & & \end{tabular} Send data to Excel $\square$ $<\mu<$ $\square$ $\square$ Ollo 用 Check Save For Later Submit Assignment

See Solution

Problem 1030

Which of the following is true regarding ANOVA?
It reaches a conclusion regarding differences among the variances of each group.
Analysis begins with the sum of squares error (SSE) as the starting point.
Equality of variances is tested using the Tukey-Kramer Procedure It uses the promciple of partitioning to subdivide the sources of variation

See Solution

Problem 1031

Suppose that a simple random sample of size $n=315$ selected from a population has $x=185$ successes. Calculate the margin of error for a $95 \%$ confidence interval for the proportion of successes for the population, $p$ . Compute the sample proportion, $\hat{p}$ , standard error estimate, SE, critical value, $z$ , and the margin of error, $m$ . Use a $z$ -distribution table to determine the critical value. Give all of your answers to three decimal places except give the critical value, $z$ , to two decimal places. $\hat{p}=$ $\square$ $\mathrm{SE}=$ $\square$ $z=$ $\square$ $m=$ $\square$

See Solution

Problem 1032

a. In testing the common belief that the proportion of male babies is equal to 0.512 , identify the values of $\hat{p}$ and $p$ . $\hat{p}=$ $\square$ $\mathrm{p}=$ $\square$ (Round to three decimal places as needed.) (Round to three decimal places as needed.) A. Those that are both grester than or equal to $\square$ and less than or equal to $\square$ B. Those that are greater than or equal to $\square$ C. Those that are less than or equal to $\square$ D. Those that are less than or equal to $\square$ and those that are greater than or equal to $\square$ -
There $\square$ sufficient evidence to $\square$ the claim that the proportion of male births is equal to 0.512 .

See Solution

Problem 1033

UUESTION TWO (20 MARKS) The following data relate to advertisement expenditure(in thousands of shillings) and their correspondin sales( in a hundred thousand shillings) \begin{tabular}{|c|c|c|c|c|c|c|c|} \hline Advertisement Expenditure & 40 & 50 & 38 & 60 & 65 & 50 & 35 \\ \hline Sales & 38 & 60 & 55 & 70 & 60 & 48 & 30 \\ \hline \end{tabular} a) Fit a linear regression equation for sales on advertisement expenditure. (6 marks) a) Estimate the sales corresponding to advertising expenditure of KES 30, 000. (2 marks) b) Determine the Pearson's correlation coefficient. (5 marks) c) Compute the coefficient of determination. (2 marks) d) Obtain the Analysis of Variance (ANOVA) table. (6 marks)
OUESTION THREE (20 MARKS)

See Solution

Problem 1034

5 For a $90 \%$ confidence interval for proportion $p$ , with $n=100$ and $x=38$ a. Determine $\mathbf{Z}_{\alpha 2}$ , p-hat, and E . b. State and interpret the resultant $90 \%$ confidence interval.

See Solution

Problem 1035

A newspaper published an article about a study in which researchers subjected laboratory gloves to stress. Among 281 vinyl gloves, $70 \%$ leaked viruses. Among 281 latex gloves, $6 \%$ leaked viruses. Using the accompanying display of the technology results, and using a 0.10 significance level, test the claim that vinyl gloves have a greater virus leak rate than latex gloves. Let vinyl gloves be population 1.
What are the null and alternative hypotheses? A. $H_{0}: P_{1}<P_{2}$ $H_{1}: p_{1}=p_{2}$ D. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1} \neq p_{2}$ B. $H_{0}: p_{1}=p_{2}$ C. $H_{0}: p_{1}>p_{2}$ $H_{1}: p_{1}>p_{2}$ $H_{1}: p_{1}=p_{2}$ E. $H_{0}: p_{1}=p_{2}$ F. $H_{0}: p_{1} \neq p_{2}$ $H_{1}: p_{1}<p_{2}$
Identify the test statistic. 15.64 (Round to two decimal places as needed.) Identify the P -value. $\square$ (Round to three decimal places as needed.)

See Solution

Problem 1036

Use the sample data and confidence level given below to complete parts (a) through (d).
A drug is used to help prevent blood clots in certain patients. In clinical trials, among 4571 patients treated with the drug, 112 developed the adverse reaction of nausea. Construct a $90 \%$ confidence interval for the proportion of adverse reactions. a) Find the best point estimate of the population proportion $p$ . $\square$ (Round to three decimal places as needed.) b) Identify the value of the margin of error E . $\mathrm{E}=\square$ (Round to three decimal places as needed.) c) Construct the confidence interval. $\square$ $\square$ $<p<$ (Round to three decimal places as needed.)

See Solution

Problem 1037

A study was conducted to determine the proportion of people who dream in black and white instead of color. Anong 324 people over the age of 55, 66 dream in black and white, and among 293 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 65 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 altemative hypotheses for the hypothesis test? A. $H_{0}: p_{1}=p_{2}$ B. $H_{0}: p_{1} \leq p_{2}$ C. $H_{0}: p_{1} \geq p_{2}$ $H_{1}: p_{1}<p_{2}$ $H_{1}: p_{1} \neq p_{2}$ $H_{1}: p_{1} \neq p_{2}$ D. $H_{0}: p_{1} \neq p_{2}$ E. $H_{0}: p_{1}=p_{2}$ F. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1}=p_{2}$ $H_{1}: p_{1}>p_{2}$ $\begin{array}{l} H_{0}: p_{1}=p_{2} \\ H_{1}: p_{1} \neq p_{2} \end{array}$

See Solution

Problem 1038

A study was conducted to determine the proportion of people who dream in black and white instead of color. Among 308 people over the age of 55, 66 dream in black and white, and among 286 people under the age of 25,20 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. $H_{0}: p_{1} \leqslant p_{2}$ C. $H_{0}: p_{1}=p_{2}$ $H_{1}: p_{1}<p_{2}$ $H_{1}: p_{1} \neq p_{2}$ $H_{1}: p_{1}>p_{2}$
$\text { D. } \begin{array}{l} H_{0}: p_{1} \neq p_{2} \\ H_{1}: p_{1}=p_{2} \end{array}$ E. $H_{0}: p_{1}=p_{2}$ F. $H_{0}: p_{1} \geq p_{2}$ $H_{1}: p_{1} \neq p_{2}$ $H_{1}: p_{1} \neq p_{2}$
Identify the test statistic. $\mathrm{z}=\square$ (Round to two decimal places as needed.)

See Solution

Problem 1039

\begin{align} \text{We have the following data extracted from StatKey:} \\ \text{Original Sample:} \\ n &= 200, \\ \text{mean} &= 98.925, \\ \text{median} &= 96, \\ \text{stdev} &= 26.83. \\ \text{Randomization Sample:} \\ n &= 200, \\ \text{mean} &= 76.015, \\ \text{median} &= 73.075, \\ \text{stdev} &= 28.062. \\ \text{Null hypothesis: } \mu &= 72. \\ \text{Construct a 95\% confidence interval for the population mean.} \end{align}

See Solution

Problem 1040

A random sample of 11 employees produced the following data, where $x$ is the number of years of experience, and $y$ is the salary (in thousands of dollars). The data are presented below in the table of values. \begin{tabular}{cc} $x$ & $y$ \\ 12 & 38 \\ 15 & 30 \\ 17 & 39 \\ 19 & 35 \\ 20 & 36 \\ 23 & 58 \\ 25 & 42 \\ 27 & 62 \\ 29 & 65 \\ 30 & 63 \\ 32 & 51 \end{tabular}
What is the value of the intercept of the regression line, $b$ , rounded to one decimal place?
Provide your answer below:

See Solution

Problem 1041

Data on the weights (b) of the contents of cans of diet soda versus the contents of cans of the regular version of the soda is summarized to the right. Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. Complete parts (a) and (b) below. Use a 0.01 significance level for both parts. \begin{tabular}{|c|c|c|} \hline & Diet & Regular \\ \hline $\boldsymbol{\mu}$ & $\mu_{1}$ & $\mu_{2}$ \\ \hline $\mathbf{n}$ & 32 & 32 \\ \hline $\overline{\mathbf{x}}$ & 0.79654 lb & 0.81963 lb \\ \hline $\mathbf{s}$ & 0.00432 lb & 0.00754 lb \\ \hline \end{tabular}
The test statistic, t , is -15.03 . (Round to two decimal places as needed.) The P-value is 0.000 . (Round to three decimal places as needed.) State the conclusion for the test. A. Fail to reject the null hypothesis. There is not sufficient evidence to support the claim that the cans of diet soda have mean weights that are lower than the mean weight for the regular soda. B. Fail to reject the null hypothesis. There is sufficient evidence to support the claim that the cans of diet soda have mean weights that are lower than the mean weight for the regular soda. C. Reject the null hypothesis. There is sufficient evidence to support the claim that the cans of diet soda have mean weights that are lower than the mean weight for the regular soda. D. Reject the null hypothesis. There is not sufficient evidence to support the claim that the cans of diet soda have - mean weights that are lower than the mean weight for the regular soda.

See Solution

Problem 1042

Listed below are the numbers of words spoken in a day by each member of eight different randomly selected couples. Complete parts (a) and (b) below. \begin{tabular}{lcccccccc} \hline Male & 15,890 & 25,564 & 1408 & 7950 & 18,542 & 15,146 & 14,229 & 25,967 \\ \hline Female & 24,647 & 13,482 & 18,166 & 17,593 & 12,701 & 17,094 & 16,460 & 18,587 \\ \hline \end{tabular}
In this example, $\mu_{d}$ is the mean value of the ditferences a tor the population of all pairs of data, where each individual difference $d$ is defined as the words spoken by the male minus words spoken by the female. What are the null and alternative hypotheses for the hypothesis test? $H_{0}: \mu_{d}=0$ word(s) $H_{1}: \mu_{d}<0$ word(s) (Type integers or decimals. Do not round.) Identify the test statistic. $\mathrm{t}=$ $\square$ (Round to two decimal places as needed.)

See Solution

Problem 1043

Fast computer: Two microprocessors are compared on a sample of 6 benchmark codes to determine whether there is a difference in speed. The times (in seconds) used by each processor on each code are as follows: \begin{tabular}{ccccccc} \hline & \multicolumn{6}{c}{ Code } \\ \hline & 1 & 2 & 3 & 4 & 5 & 6 \\ \hline Processor A & 28.9 & 17.1 & 21.8 & 17.6 & 20.5 & 26.4 \\ \hline Processor B & 22.4 & 18.1 & 28.9 & 28.4 & 24.7 & 27.5 \\ \hline \end{tabular} Send data to Excel
Part: $0 / 2$
Part 1 of 2 (a) Find a $98 \%$ confidence interval for the difference between the mean speeds. Let $d$ represent the speed of processor A minus the speed of processor B . Use the TI-84 Plus calculator. Round the answers to two decimal places.
A 98\% confidence interval for the difference between the mean speeds is $\square$ $<\mu_{d}<$ $\square$ .

See Solution

Problem 1044

Brake wear: For a sample of 9 automobiles, the mileage (in 1000 s of miles) at which the original front brake pads were worn to $10 \%$ of their original thickness was measured, as was the mileage at which the original rear brake pads were worn to $10 \%$ of their original thickness. The results were as follows: \begin{tabular}{ccc} \hline Car & Rear & Front \\ \hline 1 & 41.6 & 32.6 \\ 2 & 35.8 & 26.7 \\ 3 & 46.4 & 37.9 \\ 4 & 46.2 & 36.9 \\ 5 & 38.8 & 29.9 \\ 6 & 51.8 & 42.3 \\ 7 & 51.2 & 42.5 \\ 8 & 44.1 & 33.9 \\ 9 & 47.3 & 36.1 \\ \hline \end{tabular} Send data to Excel
Part: $0 / 2$
Part 1 of 2 (a) Construct a $90 \%$ confidence interval for the difference in mean lifetime between the front and rear brake pads. Let $d$ represent the mileage of the rear pads minus the mileage of the front ones. Round the answers to two decimal places.
A $90 \%$ confidence interval for the mean difference in lifetime between front and rear brake pads is $\square$ $<\mu_{d}<$ $\square$ .

See Solution

Problem 1045

A high school principal wanted to know if there was a difference in absences for 9 th grade, 10 th grade, 11 th grade, or 12 th grade among students with less than a 2.0 GPA. She took a random sample of $\mathrm{n}=5$ students from each grade and compared absences among the four grades using ANOVA. The data are below: \begin{tabular}{|c|c|c|c|} \hline 9 th grade & 10th grade & 11 th grade & 12 th grade \\ \hline 6 & 10 & 17 & 15 \\ 9 & 12 & 8 & 16 \\ 6 & 11 & 11 & 12 \\ 7 & 11 & 14 & 12 \\ 7 & 14 & 15 & 12 \\ \hline \end{tabular}
2. Calculate the degrees of freedom Between Groups $\left(\mathrm{df}_{\mathrm{BG}}\right)$
3. Calculate the degrees of freedom Within Group ( $\mathrm{df}_{\mathrm{WG}}$ )
4. Calculate the Sum of Squares total ( $\mathrm{SS}_{\text {tot }}$ )
5. Calculate the Sum of Squares Between Groups $\left(\mathrm{SS}_{\mathrm{BG}}\right)$
6. Calculate Sum of Squares Within Groups (SSWG)
7. Calculate Mean Square Between Group $\left(\mathrm{MS}_{\mathrm{BG}}\right)$
8. Calculate Mean Square Within Group (MSwG)
9. Calculate the F statistic
10. Using the table in the back of the book, find the critical value for $F$ ( $\mathrm{F}_{\text {crit }}$ ) with $\alpha=.05$
11. Calculate the Tukey HSD (using $\alpha=.05$ )
12. Which of the following is the appropriate statistical conclusion?

See Solution

Problem 1046

Absorption rates: In a study to compare the absorption rates of two antifungal ointments (labeled " A " and " B "), equal amounts of the two drugs were applied to the skin of 14 volunteers. After six hours, the amounts absorbed into the skin (in $\mu \mathrm{g} / \mathrm{cm}^{2}$ ) were measured. The results were as follows: \begin{tabular}{ccc} \hline Subject & A & B \\ \hline 1 & 3.31 & 2.34 \\ 2 & 2.38 & 2.45 \\ 3 & 2.82 & 2.40 \\ 4 & 2.03 & 2.70 \\ 5 & 2.26 & 1.98 \\ 6 & 3.57 & 1.88 \\ 7 & 3.27 & 2.75 \\ 8 & 3.65 & 1.57 \\ 9 & 2.74 & 1.94 \\ 10 & 3.28 & 2.51 \\ 11 & 3.73 & 2.55 \\ 12 & 4.34 & 2.09 \\ 13 & 3.59 & 2.62 \\ 14 & 3.45 & 2.48 \\ \hline \end{tabular} Send data to Excel
Part: $0 / 2$
Part 1 of 2 (a) Construct a $98 \%$ confidence interval for the mean difference between the amounts absorbed. Let $d$ represent the amount absorbed by drug A minus the amount absorbed by drug B. Use the TI-84 Plus calculator and round the answers to three decimal places.
A 98\% confidence interval for the mean difference between the amounts absorbed is $\square$ $<\mu_{d}<$ $\square$ .

See Solution

Problem 1047

A doctor wants to estimate the mean HDL cholesterol of all 20 - to 29 -year-old females. How many subjects are needed to estimate the mean HDL cholesterol within 4 points with $99 \%$ confidence assuming $\mathrm{s}=11.6$ based on earlier studies? Suppose the doctor would be content with $90 \%$ confidence. How does the decrease in confidence affect the sample size required?
Click the icon to view a partial table of critical values.
A $90 \%$ confidence level requires 23 subjects. (Round up to the nearest subject.) How does the decrease in confidence affect the sample size required? A. Decreasing the confidence level decreases the sample size needed. B. The sample size is the same for all levels of confidence. C. Decreasing the confidence level increases the sample size needed.

See Solution

Problem 1048

$a_{1}{ }_{1}$ What is the correlation coefficient of the linear fit of the data shown below, to the nearest hundredth? (1) 1.00 (3) -0.93 (2) 0.93 (4) -1.00

See Solution

Problem 1049

Any basketball fan knows that Shaquille O'Neal, one of the NBA's most dominant centers of the last twenty years, always had difficulty shooting free throws. Over the course of his career, his overall made free-throw percentage was $53.3 \%$ . During one off season, Shaq had been working with an assistant coach on his free-throw technique. During the next season, a simple random sample showed that Shaq made 26 of 39 free-throw attempts. Test the claim at the 0.05 SL that Shaq has significantly improved his free-throw shooting. $H_{0}: p=\quad-0.533$ $\mathrm{H}_{\mathrm{a}}$ :p $=$ $\square$ 0.533 p-hat: $\square$ 0.667

See Solution

Problem 1050

- Doise leved at various area urban haspital wre messarnal in decibols samplestandard deviation from aprevious study was 8 decibel emen of the reise leuds in 26 rond ouly selected corridars was 61.2 disible d a $95 \%$ contidace intored of the true mom (Sample men) same but $98 \%$ $\begin{array}{l} s=8 \\ 7=61.2 \\ n=23 \end{array}$ b-distribuation

See Solution

Problem 1051

The following data represent the muzzle velocity (in feet per second) of rounds fired from a 155-mm gun. For each round, two measurements of the velocity were recorded using two different measuring devices, resulting in the following data. Complete parts (a) through (d) below. \begin{tabular}{lcccccc} Observation & $\mathbf{1}$ & $\mathbf{2}$ & $\mathbf{3}$ & $\mathbf{4}$ & $\mathbf{5}$ & $\mathbf{6}$ \\ A & 792.1 & 793.4 & 792.3 & 790.5 & 791.8 & 791.4 \\ B & 794.9 & 791.6 & 799.8 & 788.2 & 794.0 & 788.8 \end{tabular} C. Two measurements $(A$ and $B)$ are taken on the same round. D. All the measurements came from rounds fired from the same gun. (b) Is there a difference in the measurement of the muzzle velocity between device $A$ and device $B$ at the $\alpha=0.01$ level of significance? Note: A normal probability plot and boxplot of the data indicate that the differences are approximately normally distributed with no outliers. Let $d_{i}=A_{i}-B_{i}$ . Identify the null and alternative hypotheses. $\begin{array}{l} H_{0}: \mu_{d}=0 \\ H_{1}: \mu_{d} \neq 0 \end{array}$
Determine the test statistic for this hypothesis test. $t_{0}=-0.60$ (Round to two decimal places as needed.) Find the P -value. P-value $=\square$ (Round to three decimal places as needed.)

See Solution

Problem 1052

CONFIDENTIAL DEC2024/ECO545
PART B (30 MARKS) QUESTION 1 Farah Ahmad is studying the relationship between students' final exam scores $Y_{i}$ (measured in GPA) and their hours spent studying per week $X_{i}$ (measured in hours). The population regression equation is given by: $Y i=\beta_{0}+\beta_{1} X_{i}+\mu$
Preliminary analysis of the sample data produces the following statistics: $\begin{array}{l} \sum Y=48095 \quad \sum X=95050 \quad \sum Y^{2}=406538 \quad \sum e=5807 \\ \quad \sum X^{2}=354446 \quad \sum X Y=1554698 \quad n=1200 \end{array}$
Use the above information to answer the following questions. a) Estimate the regression slope and intercept (6 marks) b) Write the estimated regression equation (1 mark) c) Interpret the estimated slope coefficient. (2 marks) d) Compute the coefficient determination and interpret it. (4 marks) e) Predict the exam score if the student spends 5 hours per week of studying. (2 marks)

See Solution

Problem 1053

Identify one fact about fibula lengths given the least relative frequency of 0.01 and highest frequency in 35-36 cm range.
A. About two-thirds of females have a length between 31 and 35 cm. B. About $25 \%$ of females have a length between 32 and 33 cm. C. About two-thirds of females have a length between 36 and 40 cm. D. About $25 \%$ of females have a length between 35 and 36 cm.

See Solution

Problem 1054

If brand $A$ has scattered residuals and brand $B$ has clustered residuals, what can we conclude about their linearity?

See Solution

Problem 1055

In February 2008, an organization surveyed 1040 adults aged 18 and older and found that 535 believed they would not have enough money to live comfortably in retirement. Does the sample evidence suggest that a majority of adults in a certain country believe they will not have enough money in retirement? Use the $\alpha=0.1$ level of significance.
Formula sheet What are the null and alternative hypotheses? $\mathrm{H}_{0}$ : p $\square$ $\square$ versus $\mathrm{H}_{1}$ : p $\square$ $\square$ Use technology to find the P -value. P -value $=$ $\square$ (Round to four decimal places as needed.) Choose the correct answer below. A. Since $P$ -value $>\alpha$ , do not reject the null hypothesis and conclude that there is not sufficient evidence that a majority of adults in the United States believe they will not have enough money in retirement. B. Since $P$ -value $<\alpha$ , do not reject the null hypothesis and conclude that there is sufficient evidence that a majority of adults in the United States believe they will not have enough money in retirement. C. Since $P$ -value $>\alpha$ , reject the null hypothesis and conclude that there is not sufficient evidence that a majority of adults in the United States believe they will not have enough money in retirement. D. Since P -value $<\alpha$ , reject the null hypothesis and conclude that there is sufficient evidence that a majority of adults in the United States believe they will not have enough money in retirement.

See Solution

Problem 1056

The following table gives the 2019 total payroll (in millions of dollars) and the percentage of games won during the 2019 season by each of the National League baseball teams. \begin{tabular}{|l|c|c|} \hline Team & \begin{tabular}{l} Total Payroll \\ (millions of dollars) \end{tabular} & \begin{tabular}{l} Percentage of \\ Games Won \end{tabular} \\ \hline Arizona Diamondbacks & 108 & 52.5 \\ \hline Atlanta Braves & 111 & 59.9 \\ \hline Chicago Cubs & 208 & 51.9 \\ \hline Cincinnati Reds & 129 & 46.3 \\ \hline Colorado Rockies & 149 & 43.8 \\ \hline Los Angeles Dodgers & 153 & 65.4 \\ \hline Miami Marlins & 63 & 35.2 \\ \hline Milwaukee Brewers & 130 & 54.9 \\ \hline New York Mets & 162 & 53.1 \\ \hline Philadelphia Phillies & 172 & 50.0 \\ \hline Pittsburgh Pirates & 66 & 42.6 \\ \hline St. Louis Cardinals & 150 & 56.2 \\ \hline San Diego Padres & 94 & 43.2 \\ \hline San Francisco Giants & 138 & 47.5 \\ \hline Washington Nationals & 181 & 57.4 \\ \hline \end{tabular}
Source: www.cbssports.com
Compute the coefficient of determination, $\rho^{2}$ , with percentage of games won as the dependent variable. (Note that this data set belongs to a population.)
Carry out all calculations exactly, and round the final answer to three decimal places. $\rho^{2}=$ $\square$

See Solution

Problem 1057

Researchers thinks that two plant species depend on each other. Wherever one grows, many times ihey observe that the other plant grows there as well.
The researchers divided a big plot of land into squares of size 1 square meter and checked whether only one of the plant species were present or both or neither. The observed values are: \begin{tabular}{|l|l|l|} \hline & Species A present & Species A not present \\ \hline Species B present & 168 & 46 \\ \hline Species B not present & 32 & 51 \\ \hline \end{tabular}
The p-value of the chi-square test of independence is less than $1 \%$ . What is the correct conclusion? We have strong evidence that the two species are dependent. We have strong evidence that the two species are independent. We don't have evidence that the two species are dependent. We don't have evidence that the two species are independent.

See Solution

Problem 1058

Decide which hypdethesis test is appropriale to use. Food researchers wanted to Investigate whe ther the acidity level of medium roasted coffee depends on the origin of coffee for 4 regions: Costa Rica, Columbia, Ethiopia, and Brazil. Hypothesis testing for one population proportion Hypothesis testing for one population mean Hypothesis testing comparing two population proportions Hypothesis testing comparing two population means - independent samples Hypothesis testing comparing two population means - matched pair samples ANOVA Chi-square test of independence T-test for linear relationship

See Solution

Problem 1059

Find the critical value and rejection region for the type of $t$ -test with level of significance $\alpha$ and sample size $n$ . Right-tailed test, $\alpha=0.1, n=35$ A. $t_{0}=-1.307 ; t<-1.307$ B. $t_{0}=1.306 ; t>1.306$ C. $t_{0}=2.441 ; t>2.441$ D. $t_{0}=1.307 ; t>1.307$

See Solution

Problem 1060

Calcium is essential to tree growth. In 1990, the concentration of calcium in precipitation in Chautauqua, New York, was 0.11 milligram per liter $\left(\frac{\mathrm{mg}}{\mathrm{L}}\right)$ . A random sample of 8 precipitation dates in 2018 results in the following data: $\begin{array}{llllllll} 0.126 & 0.183 & 0.120 & 0.234 & 0.313 & 0.108 & 0.065 & 0.087 \end{array}$
A normal probability plot suggests the data could come from a population that is normally distributed. A boxplot does not show any outliers. Does the sample evidence suggest th calcium concentrations have changed since 1990? Use the $a=0.01$ level of significance.
What are the null and altemative hypotheses? $\mathrm{H}_{0}$ $\square$ $\square$ 0.11 $\mathrm{H}_{1}$ $\boldsymbol{\mu}$ $\neq$ 0.11 (Type integers or decimals. Do not round.) Find the test statistic. $\mathrm{t}_{0}=$ $\square$ (Round to two decimal places as needed.)

See Solution

Problem 1061

To test $H_{0}: \mu=20$ versus $H_{1}: \mu<20$ , a simple random sample of size $n=18$ 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 $\bar{x}=18$ and $s=4.1$ , compute the test statistic. $\mathrm{t}=$ $\square$ (Round to two decimal places as needed.)

See Solution

Problem 1062

Submit test
A random sample of 86 eighth grade students' scores on a national mathematics assessment test has a mean score of 284. This test result prompts a state school ad to declare that the mean score for the state's eighth graders on this exam is more than 280 . Assume that the population standard deviation is 35 . At $\alpha=0.11$ , is there evidence to support the administrator's claim? Complete parts (a) through (e). (b) Find the standardized test statistic $z$ . $z=1.06$ (Round to two decimal places as needed.) (c) Find the P -value. $P$ -value $=0.145$ (Round to three decimal places as needed.) (d) Decide whether to reject or fail to reject the null hypothesis. Reject $\mathrm{H}_{0}$ Fail to reject $\mathrm{H}_{0}$ (e) Interpret your decision in the context of the original claim.
At the $11 \%$ significance level, there 280. $\square$ enough evidence to $\square$ the administrator's claim that the mean score for the state's eighth graders on the exam is more

See Solution

Problem 1063

. 3 Testing a Claim About a Question 8, 8.3.22-T HW Score: $66.11 \%, 5.95$ of 9 points Part 2 of 4 Points: 0 of 1 Save
Students estimated the length of one minute without reference to a watch or clock, and the times (seconds) are listed below. Assume that a simple random sample has been selected. Use a 0.05 significance level to test the claim that these times are from a population with a mean equal to 60 seconds. Does it appear that students are reasonably good at estimating one minute? \begin{tabular}{llllllll} 70 & 83 & 38 & 65 & 41 & 22 & 59 & 62 \\ 68 & 50 & 62 & 71 & 98 & 92 & 65 & \end{tabular}
Perform the test assuming that the requirements are met. Identify the null and alternative hypotheses. $\begin{array}{l} H_{0}: \mu=60 \\ H_{1}: \mu \neq 60 \end{array}$ (Type integers or decimals. Do not round.) Identify the test statistic. $\square$ (Round to two decimal places as needed.)

See Solution

Problem 1064

Recently, a health organization estimated that the flu vaccine was $56 \%$ effertive against the influenza B virus. An immunologist suspects that the current flu vaccine is less effective against this virus. Pick the correct pair of hypotheses the immunologist could use to test this claim.
Choose the correct answer below. A. $H_{0}: p>0.56$ $H_{a}: p<0.56$ B. $H_{0}: p=0.56$ $H_{a}: p<0.56$ C. $H_{0}: p=0.56$ $H_{a}: p \neq 0.56$ D. $H_{0}: p=0.56$ $H_{a}: p>0.56$

See Solution

Problem 1065

10 11 12 13 14 15 16 17 18 Español 19
House prices: Data from the Denver Metro Association of Realtors indicates that the mean price of a home in Denver, Colorado, in 2018 was 260.7 thousand dollars. A random sample of 60 homes sold in 2019 had a mean price of 293 thousand dollars. Can you conclude that the mean price in 2019 is greater than the mean price in 2018? Assume the population standard deviation is $\sigma=155$ . Use the $\alpha=0.10$ level of significance and the $P$ -value method with the TI-84 Plus calculator.
Part: $0 / 7$
Part 1 of 7 (a) State the appropriate null and alternate hypotheses. $\begin{array}{l} H_{0}=\square \\ H_{1}=\square \end{array}$
This hypothesis test is a (Choose one) test. $\square$

See Solution

Problem 1066

Submit test
A scientist claims that pneumonia causes weight loss in mice. The table shows the weights (in grams) of six mice before infection and two days after infection. At $\alpha=0.05$ , is there enough evidence to support the scientist's claim? Assume the samples are random and dependent, and the population is normally distributed. Complete parts (a) through (e) below. \begin{tabular}{|l|c|c|c|c|c|c|} \hline Mouse & $\mathbf{1}$ & $\mathbf{2}$ & $\mathbf{3}$ & $\mathbf{4}$ & $\mathbf{5}$ & $\mathbf{6}$ \\ \hline Weight (before) & 23.8 & 20.7 & 21.8 & 22.8 & 19.2 & 22.4 \\ \hline Weight (after) & 23.7 & 20.8 & 21.7 & 22.8 & 19.0 & 22.4 \\ \hline \end{tabular} (a) Identify the claim and state $\mathrm{H}_{0}$ and $\mathrm{H}_{\text {a }}$ .
What is the claim? A. Weight gain causes pneumonia in mice. B. Pneumonia causes weight loss in mice. C. Pneumonia causes weight gain in mice. D. Weight loss causes pneumonia in mice.
Let $\mu_{d}$ be the hypothesized mean of the difference in the weights (before-after). What are $\mathrm{H}_{0}$ and $\mathrm{H}_{\mathrm{a}}$ ? A. $H_{0}: \mu_{d} \neq 0$ B. $H_{0}: \mu_{d}=0$ C. $H_{0}: \mu_{d} \geq \bar{d}$ $H_{a}: \mu_{d}=0$ $H_{a}: \mu_{d} \neq 0$ $H_{a}: \mu_{d}<\bar{d}$ D. $H_{0}: \mu_{d} \geq 0$ E. $H_{0}: \mu_{d} \leq 0$ $H_{a}: \mu_{d}<0$ $H_{a}: \mu_{d}>0$ F. $H_{0}: \mu_{d} \leq \bar{d}$ $H_{a}: \mu_{d}>\bar{d}$ (b) Find the critical value(s) and identify the rejection region(s).
Select the correct choice below and fill in any answer boxes to complete your choice. (Round to three decimal places as needed.) A. $\mathrm{t}<$ $\square$ B. $t>$ $\square$

See Solution

Problem 1067

Submit test
A scientist claims that pneumonia causes weight loss in mice. The table shows the weights (in grams) of six mice before infection and two days after infection. At $\alpha=0.05$ , is there enough evidence to support the scientist's claim? Assume the samples are random and dependent, and the population is normally distributed. Complete parts (a) through (e) below. \begin{tabular}{|l|c|c|c|c|c|c|} \hline Mouse & 1 & $\mathbf{2}$ & $\mathbf{3}$ & $\mathbf{4}$ & $\mathbf{5}$ & $\mathbf{6}$ \\ \hline Weight (before) & 23.8 & 20.7 & 21.8 & 22.8 & 19.2 & 22.4 \\ \hline Weight (after) & 23.7 & 20.8 & 21.7 & 22.8 & 19.0 & 22.4 \\ \hline \end{tabular} (D) rina ine critical value(s) and iaentiry the rejection region(s).
Select the correct choice below and fill in any answer boxes to complete your choice. (Round to three decimal places as needed.) A. $t<$ - $\square$ B. $t>$ $\square$ C. $\mathrm{t}<$ $\square$ or $t>$ $\square$ (c) Calculate $\overline{\mathrm{d}}$ and $\mathrm{s}_{\mathrm{d}}$ . $\bar{d}=$ $\square$ (Round to three decimal places as needed.)
Calculate $\mathrm{s}_{\mathrm{d}}$ . $s_{d}=$ $\square$ (Round to three decimal places as needed.) (d) Find the standardized test statistic t . $\square$ $\mathrm{t}=$ (Round to two decimal places as needed.) (e) Decide whether to reject or fail to reject the null hypothesis and interpret the decision in the context of the original claim. $\square$ the null hypothesis. There $\square$ enough evidence to $\square$ the claim that $\square$ causes $\square$ in mice.

See Solution

Problem 1068

Given a sample with $r=0.823, n=10$ , and $\alpha=0.05$ , determine the critical values $t_{0}$ necessary to test the claim $\rho=0$ . $\qquad$ A. $\pm 1.833$ B. $\pm 2.821$ C. $\pm 1.383$ D. $\pm 2.306$

See Solution

Problem 1069

Given the data:
$\begin{array}{ccccccccccc} x & -5 & -3 & 4 & 1 & -1 & -2 & 0 & 2 & 3 & -4 \\ y & -10 & -8 & 9 & 1 & -2 & -6 & -1 & 3 & 6 & -8 \end{array}$
Use the regression equation to predict the value of $y$ for $x = 2.6$ . Assume that the variables $x$ and $y$ have a significant correlation.
The formula for the slope is:
$b_{1}=\frac{n \sum(x y)-\sum x \sum y}{n \sum x^{2}-\left(\sum x\right)^{2}}$
And for the intercept:
$b_{0}=\bar{y}-b_{1} \bar{x}$
Choose the correct prediction from the following options: A. 3.532 \\ B. 4.900 \\ C. 6.004 \\ D. 0.662

See Solution

Problem 1070

was conducted to compare the new method with the mandard procetrae. new method and emey were trained for a period of three weeks, one growip wingthe required for and the other following standard training procedure. The lenght of time in rimaes period. The employee to assemble the device was recorded at the end of the threewerk. period. The measurements are given in the following table: \begin{tabular}{|l|c|c|c|c|c|c|c|c|c|} \hline Standard procedure & 32 & 37 & 35 & 28 & 41 & 44 & 35 & 31 & 34 \\ \hline New procedure & 35 & 31 & 29 & 25 & 34 & 40 & 27 & 32 & 31 \\ \hline \end{tabular}
Do the data present sufficient evidence to indicate that the mean time to assemble at the three-week training period is less for the new training procedure?

See Solution

Problem 1071

TASK 1 The hypothetical data below relate the heights of plants and their yields. \begin{tabular}{|l|c|c|c|c|c|c|c|} \hline Plant height (cm) & 3 & 8 & 9 & 13 & 14 & 16 & 19 \\ \hline Yield (kg) & 12 & 17 & 20 & 23 & 25 & 27 & 28 \\ \hline \end{tabular} [02] (a) Explain what is meant by correlation. [04] (b) Correlation does not necessarily imply causation. Discuss this statement. [14] (c) Compute and interpret the Pearson's correlation coefficient? [05] (d) Hence, find and interpret the coefficient of determination

See Solution

Problem 1072

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. If it is found that $\mathrm{r}=0$ , does that indicate that there is no association between these two variables?
Choose the correct answer below. A. No, because if $\mathrm{r}=0$ , the variables are in a perfect linear relationship. B. No, because r does not measure the strength of the relationship, only its direction. C. No, because while there is no linear correlation, there may be a relationship that is not linear. D. Yes, because if $\mathrm{r}=0$ , the variables are completely unrelated.

See Solution

Problem 1073

Assume that the differences are normally distributed. Complete parts (a) through (d) below. \begin{tabular}{lcccccccc} Observation & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 \\ $\mathbf{X}_{\mathbf{i}}$ & 53.7 & 51.1 & 45.8 & 42.9 & 54.7 & 48.1 & 49.4 & 51.8 \\ $\mathbf{Y}_{\mathbf{i}}$ & 54.6 & 49.2 & 47.6 & 47.7 & 54.2 & 51.8 & 52.5 & 53.6 \end{tabular} (a) Determine $d_{i}=X_{i}-Y_{i}$ for each pair of data. \begin{tabular}{lcc|c|c|c|c} Observation & 1 & 2 & 3 & 4 & 5 & 6 \\ 7 & 8 \\ \hline $\mathbf{d}_{\mathbf{i}}$ & -0.9 & 1.9 & -1.8 & -4.8 & 0.5 & -3.7 \\ \hline \end{tabular} (Type integers or decimals.) (b) Compute $\overline{\mathrm{d}}$ and $\mathrm{s}_{\mathrm{d}}$ . $\bar{d}=-1.713$ (Round to three decimal places as needed.) $\mathrm{s}_{\mathrm{d}}=2.205$ (Round to three decimal places as needed.) (c) Test if $\mu_{\mathrm{d}}<0$ at the $\alpha=0.05$ level of significance.
What are the correct null and alternative hypotheses? A. $H_{0}: \mu_{d}=0$ B. $H_{0}: \mu_{d}>0$ $\mathrm{H}_{1}: \mu_{\mathrm{d}}<0$ $\mathrm{H}_{1}: \mu_{\mathrm{d}}<0$ C. $H_{0}: \mu_{d}<0$ D. $H_{0}: \mu_{d}<0$ $\mathrm{H}_{1}: \mu_{\mathrm{d}}>0$ $H_{1}: \mu_{d}=0$

See Solution

Problem 1074

A parenting magazine reports that the average amount of wireless data used by teenagers each month is 7 Gb. For her science fair project, Ella sets out to prove the magazine wrong. She claims that the mean among teenagers in her area is less than reported. Ella collects information from a simple random sample of 4 teenagers at her high school, and calculates a mean of 5.8 Gb per month with a standard deviation of 1.9 Gb per month. Assume that the population distribution is approximately normal. Test Ella's claim at the 0.005 level of significance. Step 3 of 3: Draw a conclusion and interpret the decision. Answer

See Solution

Problem 1075

Which of the following are true? If false, explain briefly.
a) A very high $P$ -value is strong evidence that the null hypothesis is false. b) A very low $P$ -value proves that the null hypothesis is false. c) A high $P$ -value shows that the null hypothesis is true. d) A $P$ -value below $0.05$ is always considered sufficient evidence to reject a null hypothesis.
a) Choose the correct answer below. A. This statement is false because it is a low $P$ -value that provides evidence that the null hypothesis is false. B. This statement is false because a very high $P$ -value proves that the null hypothesis is false. C. This statement is false because a very high $P$ -value is strong evidence that the null hypothesis is true. D. This statement is true.
b) Choose the correct answer below. A. This statement is false because a very low $P$ -value proves that the null hypothesis is true. B. This statement is false because it is a very high $P$ -value that proves that the null hypothesis is false. C. This statement is true. D. This statement is false because a very low $P$ -value only shows strong evidence that the null hypothesis is false.
c) Choose the correct answer below. A. This statement is false because a high $P$ -value shows that the null hypothesis is false. B. This statement is true. C. This statement is false because a high $P$ -value shows that the data is consistent with the null hypothesis, but can never prove that the null hypothesis is true. D. This statement is false because a high $P$ -value shows that the data is not consistent with the null hypothesis, and can only prove that the null hypothesis is false.

See Solution

Problem 1076

Two Polish math professors and their students spun a Belgian euro coin 250 times. It landed on heads 140 times. One of the professors concluded that the coin was minted asymmetrically. A representative from the Belgian mint said that the result was just by chance. Is the math professor or the representative from the Belgian mint correct? At the 0.01 SL test the math professor's claim that the coin is not fair.
We reject the null hypothesis because we find sufficient evidence to state that the alternative hypothesis is true.
We reject the null hypothesis because we fail to find sufficient evidence to state that the alternative hypothesis is true.
We fail to reject the null hypothesis because we fail to find sufficient evidence to state that the alternative hypothesis is true.
We fail to reject the null hypothesis because we find sufficient evidence to state that the alternative hypothesis is true.

See Solution

Problem 1077

59. After once again losing a football game to the archrival, a college's alumni association conducted a survey to see if alumni were in favor of firing the coach. An SRS of 100 alumni from the population of all living alumni was taken, and 64 of the alumni in the sample were in favor of firing the coach. Suppose you wish to see if a majority of living alumni are in favor of firing the coach. The appropriate test statistic is (a) $z=\frac{0.64-0.5}{\sqrt{\frac{0.64(0.36)}{100}}}$ (d) $z=\frac{0.64-0.5}{\sqrt{\frac{0.64(0.36)}{64}}}$ (b) $t=\frac{0.64-0.5}{\sqrt{\frac{0.64(0.36)}{100}}}$ (e) $z=\frac{0.5-0.64}{\sqrt{\frac{0.5(0.5)}{100}}}$ (c) $z=\frac{0.64-0.5}{\sqrt{\frac{0.5(0.5)}{100}}}$

See Solution

Problem 1078

\begin{problem} The government conducted a study and collected the given data. Use the data to answer the following questions. \begin{tabular}{|c|c|c|c|c|} \hline Speed (mph) & 45 & 55 & 65 & 75 \\ \hline Fuel (mpg) & 43 & 45 & 38 & 32 \\ \hline \end{tabular}
Using the quadratic regression model between speed and fuel, find the residual for the person who drove 65 mph: \begin{enumerate} \item 1.5 \item $-1.5$ \item 0.5 \item 43.5 \end{enumerate} \end{problem}

See Solution

Problem 1079

Use the sample data and confidence level given below to complete parts (a) through (d). A research institute poll asked respondents if they felt vulnerable to identity theft. In the poll, $\mathrm{n}=973$ and $x=600$ who said "yes." Use a 95\% confidence level.
䏹 Click the icon to view a table of z scores. a) Find the best point estimate of the population proportion $p$ . 0.617 (Round to three decimal places as needed.) b) Identify the value of the margin of error $E$ . $E=\square$ (Round to three decimal places as needed.)

See Solution

Problem 1080

b. What point estimate can we use to construct a confidence interval for the difference between the two datasets? Include appropriate units. The point estimate we can use to construct a confidence interval for the difference between the two datasets is 3.065 . c. What is the margin of error? Include appropriate units.
The margin of error is $\pm 3.499 \%$ . d. What is the $95 \%$ confidence interval? Use interval notation.
The $95 \%$ confidence interval is $[-0.433,6.564]$ . e. Interpret the confidence interval in context of the application, using appropriate units. Confidence inteiral for the means f. Does your interval contain zero? What does this tell us about the research question? Explain your answer in the context of your research.

See Solution

Problem 1081

Let $p$ be the population proportion for the following condition. Find the point estimates for $p$ and $q$ . In a survey of 1806 adults from country A, 637 said that they were not confident that the food they eat in country $A$ is safe.
The point estimate for $p, \hat{p}$ , is $\square$ (Round to three decimal places as needed.) The point estimate for $q, \hat{q}$ , is $\square$ (Round to three decimal places as needed.)

See Solution

Problem 1082

A magazine includes a report on the energy costs per year for 32 -inch liquid crystal display (LCD) televisions. The article states that 14 randomly selected 32 -inch LCD televisions have a sample standard deviation of $\$ 3.56$ . Assume the sample is taken from a normally distributed population. Construct $90 \%$ confidence intervals for (a) the population variance $\sigma^{2}$ and (b) the population standard deviation $\sigma$ . Interpret the results. (a) The confidence interval for the population variance is $\square$ , ). (Round to two decimal places as needed.) Interpret the results. Select the correct choice below and fill in the answer box(es) to complete your choice. (Round to two decimal places as needed.) A. With $10 \%$ confidence, you can say that the population variance is between
$\square$ and $\square$ B. With $90 \%$ confidence, you can say that the population variance is less than C. With $90 \%$ confidence, you can say that the population variance is between $\square$ D. With $10 \%$ confidence, you can say that the and $\square$ population variance is greater than

See Solution

Problem 1083

Calories in Cheeseburgers The number of calories in a random selection of cheeseburgers from 10 fast food restaurants is listed. \begin{tabular}{lllll} 497 & 533 & 536 & 513 & 505 \\ 441 & 442 & 510 & 482 & 478 \end{tabular} Send data to Excel
Is there sufficient evidence to conclude that the variance differs from 700? Use the 0.01 level of significance. Assume the variables are approximately normally distributed.
Part 1 of 5 (a) State the hypotheses and identify the claim with the correct hypothesis. $\begin{array}{l} H_{0}: \sigma^{2}=700 \text { not claim } \\ H_{1}: \sigma^{2} \neq 700 \text { claim } \end{array}$
This hypothesis test is a two-tailed test.
Part 2 of 5 (b) Find the critical value(s). Round the answer(s) to at least three decimal places. If there is more than one critical value, separate them with commas. $\text { Critical value(s): } 1.735,23.589$
Part: $2 / 5$
Part 3 of 5 (c) Compute the test value. Round the answer to at least three decimal places, $x^{2}=$ $\square$

See Solution

Problem 1084

Calories in Cheeseburgers The number of calories in a random selection of cheeseburgers from 10 fast food restaurants is listed. \begin{tabular}{lllll} 497 & 533 & 536 & 513 & 505 \\ 441 & 442 & 510 & 482 & 478 \end{tabular}
Send data to Excel Is there sufficient evidence to conclude that the variance differs from 700? Use the 0.01 level of significance. Assume the variables are approximately normally distributed.
Part 1 of 5 (a) State the hypotheses and identify the claim with the correct hypothesis. $\begin{array}{l} H_{0}: \sigma^{2}=700 \text { not claim } \quad \\ H_{1}: \sigma^{2} \neq 700 \text { claim } \end{array}$
This hypothesis test is a two-tailed $\boldsymbol{\nabla}$ test.
Part 2 of 5 (b) Find the critical value(s). Round the answer(s) to at least three decimal places. If there is more than one critical value, separate them with commas.
Critical value(s): $1.735,23.589$
Part: $2 / 5$
Part 3 of 5 (c) Compute the test value. Round the answer to at least three decimal places. $\begin{array}{l} \chi^{2}= \\ \square \end{array}$

See Solution

Problem 1085

Imagine you are a business consultant who collects data for a company on employee job performance. You are particularly interested in how training and employee self-direction (autonomy) impact job performance. You evaluate employee scores on a measure of autonomy and divide them into 2 groups, low autonomy and high autonomy. Then, you measure everyone's job performance before training, then everyone's job performance after training.
5 4.5 4 Job performance 3.5 3 2.5 2 1.5 1 Low training High training
Low autonomy High autonomy
Is this a between, within, or mixed design? between subjects design mixed design within subjects design unable to determine from question

See Solution

Problem 1086

Imagine you are a business consultant who collects data for a company on employee job performance. You are particularly interested in how training and employee self-direction (autonomy) impact job performance. You evaluate employee scores on a measure of autonomy and divide them into 2 groups, low autonomy and high autonomy. Then, you measure everyone's job performance before training, then everyone's job performance after training.
Based on the figure above, Do there appear to be any Main Effects? No, there are seemingly no main effects Yes, there is seemingly a main effect for training Yes, there is seemingly a main effect for both training (IV 1) and autonomy (IV 2) Yes, there is seemingly a main effect for autonomy

See Solution

Problem 1087

A variety of summary statistics were collected for a small sample of bivariate data, where the dependent variable was $y$ and an independent variable was $x$ . $\sum x = 90$ , $\sum y = 170$ , $n = 10$ , $\sum[(x - \overline{x})(y - \overline{y})] = 466$ , $\sum[(x - \overline{x})^2] = 234$ , and $\sum[(y-\overline{y})^2]$ Find $a$ . 0.928 -0.928 1.992 -1.992

See Solution

Problem 1088

A regression was run to determine if there is a relationship between hours of TV watched per day ( x ) and number of situps a person can do (y).
The results of the regression were: $\begin{array}{l} y=a x+b \\ a=-0.854 \\ b=29.877 \\ r^{2}=0.687241 \\ r=-0.829 \end{array}$
Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place) $\square$

See Solution

Problem 1089

Suppose that you run a correlation and find the correlation coefficient is 0.325 and the regression equation is $\hat{y}=7.8 x-21.72$ . The centroid of your data was $(5.9,24.8)$ .
If the critical value is .632 , use the appropriate method to predict the $y$ value when $x$ is 3.9 $\square$

See Solution

Problem 1090

A researcher wanted to determine if carpeted rooms contain more bacteria than uncarpeted rooms. The table shows the results for the number of bacteria per cubic foot for both types of rooms.
Carpeted | Uncarpeted ------- | -------- 13.7 | 11.8 6.9 | 8.2 7.4 | 13.1 8.9 | 5.3 7.9 | 7.8 8.5 | 4.1 10.7 | 12.7 14.1 | 5.4
Determine whether carpeted rooms have more bacteria than uncarpeted rooms at the $\alpha = 0.01$ level of significance. Normal probability plots indicate that the data are approximately normal and boxplots indicate that there are no outliers. State the null and alternative hypotheses. Let population 1 be carpeted rooms and population 2 be uncarpeted rooms. A. $H_0: \mu_1 = \mu_2$ $H_1: \mu_1 > \mu_2$ B. \(H_0: \mu_1 < \mu

See Solution

Problem 1091

Question 5, 10.1.9 Part 2 of 6
Refer to the accompanying scatterplot. a. Examine the pattern of all 10 points and subjectively determine whether there appears to be a strong correlation between x and y. b. Find the value of the correlation coefficient $r$ and determine whether there is a linear correlation. c. Remove the point with coordinates (9,10) and find the correlation coefficient $r$ and determine whether there is a linear correlation. d. What do you conclude about the possible effect from a single pair of values?
Click here to view a table of critical values for the correlation coefficient.
a. Do the data points appear to have a strong linear correlation? Yes No
b. What is the value of the correlation coefficient for all 10 data points? $r=$ (Simplify your answer. Round to three decimal places as needed.)

See Solution

Problem 1092

Use the given data set to complete parts (a) through (c) below. (Use $\alpha = 0.05$ .)
x | 10 | 8 | 13 | 9 | 11 | 14 | 6 | 4 | 12 | 7 | 5 ---|---|---|---|---|---|---|---|---|---|---|--- y | 9.14 | 8.14 | 8.74 | 8.77 | 9.26 | 8.11 | 6.13 | 3.11 | 9.12 | 7.26 | 4.75
Click here to view a table of critical values for the correlation coefficient.
a. Construct a scatterplot. Choose the correct graph below.
b. Find the linear correlation coefficient, $r$ , then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is $r =$ \[\_\_\_\_\_] (Round to three decimal places as needed.)

See Solution

Problem 1093

The following bivariate data set contains an outlier. \begin{tabular}{|r|r|} \hline \multicolumn{1}{|c|}{ $\boldsymbol{x}$ } & $\boldsymbol{y}$ \\ \hline 73.1 & 163.8 \\ \hline 74.5 & 139.3 \\ \hline 87.7 & -42.5 \\ \hline 75.1 & 112.4 \\ \hline 80.2 & 75.1 \\ \hline 78 & 201.6 \\ \hline 70.2 & -110 \\ \hline 78.9 & 208.4 \\ \hline 70 & 96 \\ \hline 76.3 & 113.9 \\ \hline 75.3 & 166.8 \\ \hline 75.9 & -29.1 \\ \hline 79.3 & 167.1 \\ \hline 76 & -1.5 \\ \hline 140.8 & 26.6 \\ \hline \end{tabular}
What is the correlation coefficient with the outlier? $r_{w}=$ $\square$ What is the correlation coefficient without the outlier? $r_{\mathrm{wo}}=$ $\square$

See Solution

Problem 1094

Avg 28 Stdev 3 What 2 values will 95\% of days be

See Solution

Problem 1095

Avg 28 Stdev 3 What 2 values will 95% of days be

See Solution

Problem 1096

Find the critical value For confidence level of $98\%$

See Solution

Problem 1097

$\text{A sample of } 150 \text{ U.S. college students had a mean age of } 22.77 \text{ years. Assume the population standard deviation is } \sigma = 4.42 \text{ for the mean age of U.S. college students.}$ $\text{Calculate the 90\% confidence interval for the mean age of U.S. college students. Round the answers to at least two decimal places.}$

See Solution

Problem 1098

A lawncare technician believes the actual lifetime to be different than 250 hours. A test is made of $H_0: \mu = 250$ versus $H_1: \mu \neq 250$ . The null hypothesis is not rejected. State an appropriate conclusion. There (Choose one) enough evidence to conclude that the mean lifetime is (Choose one) 250 hours.

See Solution

Problem 1099

A simple random sample of size 35 has mean $x = 3.49$ . The population standard deviation is $\sigma = 1.59$ . Construct a 90% confidence interval for the population mean.
The parameter is the population mean.
The correct method to find the confidence interval is the $t$ method.

See Solution

Problem 1100

(d) The following stem-and-leaf plot illustrates a sample. 4|6 5|5 6|2 7| 8|17 9|2445 10|011245569 11|58 The stem-and-leaf plot reveals (Choose one) from an approximately normal population. Therefore, we (Choose one)

See Solution

1 ...8 9 10 11 12 13 14

Statistical Inference

Problem 1001

Problem 1002

Problem 1003

Problem 1004

Problem 1005

Problem 1006

Problem 1007

Problem 1008

Problem 1009

Problem 1010

Problem 1011

Problem 1012

Find the best predicted value of yyy given that x=5x=5x=5 for 6 pairs of data that yield r=0.444,yˉ=18.3r=0.444, \bar{y}=18.3r=0.444,yˉ​=18.3 and the regression equation y=2+5xy=2+5 xy=2+5x. State the critical level.

Problem 1013

The least squares method minimizes which of the following? All of the above SST SSE SSR

Problem 1014

Problem 1015

Problem 1016

Tina's survey of 600 students shows 53%53\%53% exercise over 30 mins daily. Why is this misleading? Choose one: outlier, small sample, biased sample, calculation error.

Problem 1017

If more driver's ed hours lead to fewer accidents, this indicates a a(n)a(n)a(n): A. negative correlation B. casual relationship C. ambiguous correlation D. positive correlation.

Problem 1018

Problem 1019

Problem 1020

Select the appropriate word or pprase to complete the sentence.The □\square□ hypothesis states that a parameter is equal to a certain value while the (Choose one) □\square□ hypothesis states that the parameter differs from this value.

Problem 1021

Problem 1022

Problem 1023

Problem 1024

Problem 1025

Problem 1026

A significant F-ratio is obtained in an ANOVA when At least two means differ significantly. All means differ significantly The sample mean differs from the population mean. The sample variance differs from the population variance.

Problem 1027

Problem 1028

Problem 1029

Problem 1030

Problem 1031

Problem 1032

Problem 1033

Problem 1034

5 For a 90%90 \%90% confidence interval for proportion ppp, with n=100n=100n=100 and x=38x=38x=38 a. Determine Zα2\mathbf{Z}_{\alpha 2}Zα2​, p-hat, and E . b. State and interpret the resultant 90%90 \%90% confidence interval.

Problem 1035

Problem 1036

Problem 1037

Problem 1038

Problem 1039

Problem 1040

Problem 1041

Problem 1042

Problem 1043

Problem 1044

Problem 1045

Problem 1046

Problem 1047

Problem 1048

a11a_{1}{ }_{1}a1​1​ What is the correlation coefficient of the linear fit of the data shown below, to the nearest hundredth? (1) 1.00 (3) -0.93 (2) 0.93 (4) -1.00

Problem 1049

Problem 1050

Problem 1051

Problem 1052

Problem 1053

Problem 1054

If brand AAA has scattered residuals and brand BBB has clustered residuals, what can we conclude about their linearity?

Problem 1055

Problem 1056

Problem 1057

Problem 1058

Problem 1059

Problem 1060

Problem 1061

Problem 1062

Problem 1063

Problem 1064

Problem 1065

Problem 1066

Problem 1067

Problem 1068

Given a sample with r=0.823,n=10r=0.823, n=10r=0.823,n=10, and α=0.05\alpha=0.05α=0.05, determine the critical values t0t_{0}t0​ necessary to test the claim ρ=0\rho=0ρ=0. \qquad A. ±1.833\pm 1.833±1.833 B. ±2.821\pm 2.821±2.821 C. ±1.383\pm 1.383±1.383 D. ±2.306\pm 2.306±2.306

Problem 1069

Find the best predicted value of $y$ given that $x=5$ for 6 pairs of data that yield $r=0.444, \bar{y}=18.3$ and the regression equation $y=2+5 x$ . State the critical level.

Tina's survey of 600 students shows $53\%$ exercise over 30 mins daily. Why is this misleading? Choose one: outlier, small sample, biased sample, calculation error.

If more driver's ed hours lead to fewer accidents, this indicates a $a(n)$ : A. negative correlation B. casual relationship C. ambiguous correlation D. positive correlation.

Select the appropriate word or pprase to complete the sentence.
The $\square$ hypothesis states that a parameter is equal to a certain value while the (Choose one) $\square$ hypothesis states that the parameter differs from this value.

5 For a $90 \%$ confidence interval for proportion $p$ , with $n=100$ and $x=38$ a. Determine $\mathbf{Z}_{\alpha 2}$ , p-hat, and E . b. State and interpret the resultant $90 \%$ confidence interval.

$a_{1}{ }_{1}$ What is the correlation coefficient of the linear fit of the data shown below, to the nearest hundredth? (1) 1.00 (3) -0.93 (2) 0.93 (4) -1.00

If brand $A$ has scattered residuals and brand $B$ has clustered residuals, what can we conclude about their linearity?

Given a sample with $r=0.823, n=10$ , and $\alpha=0.05$ , determine the critical values $t_{0}$ necessary to test the claim $\rho=0$ . $\qquad$ A. $\pm 1.833$ B. $\pm 2.821$ C. $\pm 1.383$ D. $\pm 2.306$