Select the outlier in the data set.2,71,73,83,84,87,90,92,96If the outlier were removed from the data set, would the mean increase or decrease?Choices:(A)increase(B)decrease
Q. Select the outlier in the data set.2,71,73,83,84,87,90,92,96If the outlier were removed from the data set, would the mean increase or decrease?Choices:(A)increase(B)decrease
Identify Outlier: Identify the outlier in the data set.To find the outlier, we can look for a number that is significantly different from the rest of the numbers in the set. In this case, the number 2 stands out as being much lower than all other numbers, which are all 71 or higher.
Determine Outlier: Determine if 2 is an outlier using the interquartile range (IQR) method.First, we need to find the quartiles (Q1, Q2, and Q3) of the data set. However, since the data set is small, we can visually inspect it and determine that 2 is far from the rest of the data points, which are closely grouped together. Therefore, we can consider 2 as the outlier without a formal calculation of IQR.
Calculate Mean with Outlier: Calculate the mean of the data set with the outlier.To find the mean, add all the numbers together and divide by the number of data points.Mean with outlier = (2+71+73+83+84+87+90+92+96)/9Mean with outlier = 678/9Mean with outlier = 75.33 (rounded to two decimal places)
Calculate Mean without Outlier: Calculate the mean of the data set without the outlier. Remove the outlier 2 and then add the remaining numbers together and divide by the new number of data points. Mean without outlier = (71+73+83+84+87+90+92+96)/8 Mean without outlier = 676/8 Mean without outlier = 84.5
Compare Mean: Compare the means to determine if the mean would increase or decrease when the outlier is removed.Since the mean without the outlier (84.5) is greater than the mean with the outlier (75.33), removing the outlier would increase the mean.
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