A data point that is outside the normal distribution of data,called an "outlier," is often removed from the data set before analysis because it:
A)Is obviously due to an inaccuracy in the calculations.
B)Can distort the results of the data analysis.
C)Has an upward bias on the statistical measures in regression.
D)Will always add bias to the results of a high-low analysis.

Question

Quizplus · Accepted Answer

Outliers can significantly skew the results of data analysis, especially when it comes to measures of central tendency such as the mean. Removing outliers can help ensure that the resulting analysis is more accurate and representative of the overall data set. However, it is important to exercise caution when removing outliers and to have a clear rationale for doing so.

A Data Point That Is Outside the Normal Distribution of Data,called