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Regression analysis in SPSS

a) Means, sums of squares and cross products, standard deviations, and the correlation between X and Y.
b) Regression equation of Y on X.
c) Regression and residual sum of squares.
d) F ratio for the test of significance of the regression of Y on X, using the sums of squares (i.e., SSreg and SSres) and r_xy^2.
e) Variance of estimate and the standard error of estimate.
f) Standard error of the regression coefficient.
g) T ratio for the test of the regression coefficient. What should the square of the t equal? (In other words, what statistical calculated above should it equal?)
Using the regression equations, calculate the following:
h) Each person's predicted scores, Y', on the basis of the X's (Report the first 3 subjects).
i) The sum of the predicted scores and their mean.
j) The residuals between the observed and predicted scores (y-y') for each person and their sum, ?(y-y^' ), and the sum of the squared residuals, ?(y-y')^2.
k) Plot the data, the regression line, and the standardized residuals against the predicted scores.


Solution Summary

Step by step method for computing Regression analysis in SPSS is given in the answer.