Let€™s revisit some data that we looked at in Chapter 8, in Table 8.1. Let X = Gender, coded 1 = male, 2 = female. Let Y = height. Using SPSS, run a bivariate regression to predict Height from Gender. If you do not still have your output from analyses you ran in Chapter 8 also run the Pearson correlation between Gender and Height, and the independent samples t test comparing mean heights for male and female groups.
Here is the bivariate regression to predict height from gender:

Here is the Pearson r (which could also be called a point biserial correlation) between gender and height:

Here is the independent samples t test to compare mean height for gender groups with gender coded 1 = male and 2 = female:

a. Compare the F for your bivariate regression with the t from your independent samples t test. How are these related?
b. Compare the multiple R from your bivariate regression with the r from your bivariate correlation; compare the R2 from the regression with an 2 effect size computed by hand from your t test. How are these related?
c. What do you conclude regarding these three ways of analyzing the data?

Model Summary AdjustedStd. Error of Model 766 587 581 a. Predictors: (Constant), gender ANOVAb Sum of Squares Model df Sig Mean Square 450.368 4.795 Regression 450.368 93.916 0003 316.500 766.868 a. Predictors: (Constant), gender Residual Total 67 b. Dependent Variable: height Independent Samples Test Equality of Variances t-test for E of Means dence Interval of the Difference Mean Std. Error df Sig. (2-taled) Difference Difference ariances 975 327 9.891 5.147 531 4.087 6.207 Equal variances not assumed 9.891 63 13.205 5.147 534088.208 Correlations ender gender Pearson Correlation 766* Sig. (2-tailed) 68 .766 68 height Pearson Correlation Sig. (2-tailed) 68 68 **. Correlation is significant at the 0.01 level Group Statistics Std. Std. Error gender Mean Deviation Mean height male 34 34 69.03 63.88 1.946 2.409 334 413 female Independent Samples Test Equality of Variances t-test for E of Means dence Interval of the Difference Mean Std. Error df Sig. (2-taled) Difference Difference ariances 975 327 9.891 5.147 531 4.087 6.207 Equal variances not assumed 9.891 63 13.205 5.147 534088.208