372 Statistical Methods
In this example, you use salary as the dependent variable, using four
other quantitative variables as predictors. One way to see whether female
faculty have been treated unfairly is to do the regression using just the male
data and then apply the regression to the female data. For each female fac-
ulty member, this predicts what a male faculty member would make with
the same years, age when hired, degree, and Master’s degree status. The re-
siduals are interesting because they are the difference between what each
woman makes and her predicted salary if she were a man. This assumes that
all of the relevant predictors are being used, but it would be the college’s re-
sponsibility to point out all the variables that infl uence salary in an impor-
tant way. When there is a union contract, which is the case here, it should
be clear which factors infl uence salary.Regression on Male Faculty
To do the regression on just the male faculty and then look at the residuals
for the females, use Excel’s AutoFilter capability and copy the male rows to
a new worksheet.To create a worksheet of salary information for male faculty only:1 Right-click the Salary Data sheet tab to open the pop-up menu and
then click Insert from the menu.
2 Click Worksheet from the General sheet of the Insert dialog box and
click OK.
3 Double-click the new sheet tab and type Male Faculty. Return to the
Salary Data worksheet.
4 Click the Filter button from the Sort & Filter group on the Data
tab. Excel adds drop-down arrows to all of the column headers in
the list.
5 Click the Gender drop-down arrow; then deselect all of the check-
boxes except for M and click the OK button. Excel displays only the
data for the male faculty.
6 Select the range A1:F82; then click the Copy button from the Clip-
board group on the Home tab.
7 Go to cell A1 on the Male Faculty worksheet and click the Paste
button from the Clipboard group on the Home tab. The salary data
for male faculty now occupy the range A1:F45 on the Male Faculty
worksheet.