QuestionThe data set represents the number of miles Mary jogged each day for the past nine days.
What is the outlier of the data?
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Studdy Solution
STEP 1
What is this asking? We need to find the *unusual* number in Mary's jogging data. Watch out! Don't just pick the biggest or smallest number; an outlier is a number that's *significantly* different from the others.
STEP 2
1. Arrange the Data
2. Calculate the Quartiles
3. Calculate the IQR
4. Identify the Outlier
STEP 3
Let's put the jogging distances in order from least to greatest!
This helps us see the spread of the data.
Our data is .
STEP 4
Now, let's find the **median** (the middle value).
In our ordered list, the median is .
STEP 5
Next, we'll find the **first quartile (Q1)**, the median of the lower half of the data (excluding the overall median if the dataset has an odd number of elements).
The lower half is , so Q1 is the average of and , which is .
STEP 6
Let's find the **third quartile (Q3)**, the median of the upper half of the data (excluding the overall median if the dataset has an odd number of elements).
The upper half is , so Q3 is the average of and , which is .
STEP 7
The **interquartile range (IQR)** is the difference between Q3 and Q1.
It tells us how spread out the middle of the data is.
So, IQR .
STEP 8
An outlier is typically a value that falls below or above .
Let's calculate these **boundaries**:
STEP 9
Lower boundary: .
STEP 10
Upper boundary: .
STEP 11
Any value outside these boundaries is considered an outlier.
Looking back at our data, only is less than , so is the outlier!
STEP 12
The outlier of the data set is .
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