Question

Assigned the mean of the ranks that would have been used had the scores been slightly different.

a) Rank correlation
b) Outlier treatment
c) Sensitivity analysis
d) Rank-based regression

Answer 1

Statisticians can use numerical tests involving the Interquartile Range (IQR) to identify outliers in data. If an outlier is identified, it should be removed from the dataset and the regression line and summary statistics recalculated for a better fit and improved predictions.

Step-by-step explanation:

Rather than guessing at outliers, statisticians can use numerical tests to identify them. In this case, an appropriate test involving the Interquartile Range (IQR) can be used to identify outliers in the data. In order to determine if a data value is an outlier, it is necessary to examine the residuals and compare them to two standard deviations above or below the best-fit line. If a data value is identified as an outlier, it should be treated by removing it from the dataset and recalculating the regression line and summary statistics. Deleting an outlier allows for a better fit to the remaining data points and can lead to a stronger correlation and improved predictions.