# Question

Here is a small set of (real) data that shows GNP per capita (X), and mean life satisfaction, for a set of 19 nations (Y). (Insert Table 9.2 about here)

a. Enter the data into SPSS.

b. Run the procedure; obtain the mean and standard deviation for each variable.

c. Do appropriate preliminary data screening, and then run the bivariate regression to predict life satisfaction from GNP. Write up the results in paragraph form including: statistical significance, effect size, and nature of relationship. Also use the Save command to save the unstandardized residuals as a new variable in your SPSS worksheet. Include effect size and nature of relationship even if the regression is not statistically significant.

d. Using the command, create a new variable that tells you the squared unstandardized residual for each case. Using the command, obtain the sum of the squared residuals across all 19 cases. Note that this total for sum of square residuals should correspond to SSresidual in the ANOVA table in your SPSS regression printout.

e. Show that you can use the sums of squares in the ANOVA table in the SPSS printout to reproduce the value of R2 on the SPSS printout.

a. Enter the data into SPSS.

b. Run the

c. Do appropriate preliminary data screening, and then run the bivariate regression to predict life satisfaction from GNP. Write up the results in paragraph form including: statistical significance, effect size, and nature of relationship. Also use the Save command to save the unstandardized residuals as a new variable in your SPSS worksheet. Include effect size and nature of relationship even if the regression is not statistically significant.

d. Using the

e. Show that you can use the sums of squares in the ANOVA table in the SPSS printout to reproduce the value of R2 on the SPSS printout.

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