Answer: To determine if any of these data values are outliers, you would first need to calculate the median and interquartile range (IQR) of the data set. You can then use the following rule to identify potential outliers:
- Any data value that is less than Q1 - 1.5(IQR) or greater than Q3 + 1.5(IQR) is a potential outlier.
Assuming the data set is in order, the median is 451.5 and the first and third quartiles are 389 and 495, respectively. The IQR is therefore 495 - 389 = 106. Using the rule above, we can check each data value to see if it is a potential outlier:
- 451 is not a potential outlier.
- 501 is not a potential outlier.
- 388 is not a potential outlier.
- 428 is not a potential outlier.
- 510 is not a potential outlier.
- 480 is not a potential outlier.
- 390 is not a potential outlier.
Therefore, there are no outliers in this data set.
Explanation: