To identify outliers in a data set, we first need to calculate the interquartile range (IQR).

1. Arrange the data in increasing order: 28, 76, 76, 79, 81, 83, 86, 88, 89, 91
2. Find the median (Q2). Since we have 10 data points, the median is the average of the 5th and 6th values: (81+83)/2 = 82
3. Find the lower quartile (Q1), which is the median of the first half of the data. Since we have 5 data points in the first half, the lower quartile is the 3rd value: 76
4. Find the upper quartile (Q3), which is the median of the second half of the data. Since we have 5 data points in the second half, the upper quartile is the 8th value: 88
5. Calculate the interquartile range (IQR): Q3 - Q1 = 88 - 76 = 12
6. Calculate the lower bound for outliers: Q1 - 1.5*IQR = 76 - 1.5*12 = 58
7. Calculate the upper bound for outliers: Q3 + 1.5*IQR = 88 + 1.5*12 = 106
8. Any data point that is less than the lower bound or greater than the upper bound is considered an outlier.

Looking at our data set, we can see that the value 28 is less than the lower bound (58), so it is an outlier. All other values are within the bounds, so they are not outliers.

So, the outlier in this data set is 28.

Question

To identify outliers in a data set, we first need to calculate the interquartile range (IQR).

1. Arrange the data in increasing order: 28, 76, 76, 79, 81, 83, 86, 88, 89, 91
2. Find the median (Q2). Since we have 10 data points, the median is the average of the 5th and 6th values: (81+83)/2 = 82
3. Find the lower quartile (Q1), which is the median of the first half of the data. Since we have 5 data points in the first half, the lower quartile is the 3rd value: 76
4. Find the upper quartile (Q3), which is the median of the second half of the data. Since we have 5 data points in the second half, the upper quartile is the 8th value: 88
5. Calculate the interquartile range (IQR): Q3 - Q1 = 88 - 76 = 12
6. Calculate the lower bound for outliers: Q1 - 1.5*IQR = 76 - 1.5*12 = 58
7. Calculate the upper bound for outliers: Q3 + 1.5*IQR = 88 + 1.5*12 = 106
8. Any data point that is less than the lower bound or greater than the upper bound is considered an outlier.

Looking at our data set, we can see that the value 28 is less than the lower bound (58), so it is an outlier. All other values are within the bounds, so they are not outliers.

So, the outlier in this data set is 28.

Knowee AI · Accepted Answer

To identify outliers in a data set, we first need to calculate the interquartile range (IQR).

1. Arrange the data in increasing order: 28, 76, 76, 79, 81, 83, 86, 88, 89, 91
2. Find the median (Q2). Since we have 10 data points, the median is the average of the 5th and 6th values: (81+83)/2 = 82
3. Find the lower quartile (Q1), which is the median of the first half of the data. Since we have 5 data points in the first half, the lower quartile is the 3rd value: 76
4. Find the upper quartile (Q3), which is the median of the second half of the data. Since we have 5 data points in the second half, the upper quartile is the 8th value: 88
5. Calculate the interquartile range (IQR): Q3 - Q1 = 88 - 76 = 12
6. Calculate the lower bound for outliers: Q1 - 1.5*IQR = 76 - 1.5*12 = 58
7. Calculate the upper bound for outliers: Q3 + 1.5*IQR = 88 + 1.5*12 = 106
8. Any data point that is less than the lower bound or greater than the upper bound is considered an outlier.

Looking at our data set, we can see that the value 28 is less than the lower bound (58), so it is an outlier. All other values are within the bounds, so they are not outliers.

So, the outlier in this data set is 28.

The 10 members of the swim team completed the following numbers of laps at today's practice.28, 76, 76, 79, 81, 83, 86, 88, 89, 91Identify all values that are outliers.If there is more than one outlier, separate them with commas.If there are no outliers, click on "None".

Question

Solution

Similar Questions

Upgrade your grade with Knowee