338 Statistical Methods
To calculate the correlations and p values:1 Return to the Mortality Data worksheet.
2 Enter the labels Pearson’s r, p value, Spearman’s s, and p value in
the cell range A19:A22. Enlarge the width of column A to fi t the size
of the new labels.
3 Click cell B19, type =CORREL(temperature, mortality), and press
Enter.
4 In cell B20, type =CORRELP(temperature, mortality) and press Enter.
5 In cell B21, type =SPEARMAN(temperature, mortality) and press
Enter.
6 In cell B22, type =SPEARMANP(temperature, mortality) and press
Enter.
The correlation values are shown in Figure 8-21.Figure 8-21
Correlations
and valuepThe values in Figure 8-21 indicate a strong positive correlation between
the mortality index and the mean annual temperature. The p values for both
measures are also very signifi cant, indicating that this correlation is statisti-
cally different from zero. Note that the p value for Pearson’s r is equal to the
p value for the linear regression shown earlier in Figure 8-11. One more im-
portant point: the value of r, 0.875, is equal to the square root of the R^2 statis-
tic, computed earlier in Figure 8-10. It will always be the case that R^2 is equal
to the square of Pearson’s correlation coeffi cient between two variables.
You can close the Breast Cancer Regression Analysis workbook now.
You’ve completed your analysis of the data, but you’ll return to it in the
chapter exercises.Creating a Correlation Matrix
When you have several variables to study, it’s useful to calculate the correla-
tions between the variables. In this way, you can get a quick picture of the
relationships between the variables, determining which variables are highly