Run a regression equation to predict father's education from mother's education (variable paeduc and maeduc). Include 95% confidence intervals for the slop and intercept. Save the standard error of the mean prediction. Based on this equation answer the following:
a. What do you predict for father's education for all people who have a mother with 12 year of education?
b. What do you predict for average father's education for all people who have a mother with 12 years of education?
c. Based on the results of the linear regression, can you reject the null hypothesis that there is no linear relationship between father's and mother's education?
d. Write the linear regression equation to predict father's education from mother's education.
e.What proportion of the variability in mother's education is explained by fathers education?
f. How can you tell from the slope if the correlatio coefficient between the two variables is positive or negative?
g. What can you conclude about correlation coefficient based on what you know about the slope? Can you reject the null hypothesis that population correlation coefficient is 0?
Step by step method for regression analysis of GSS is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.