Simple Regression

Question 1

What is R squared?

Answer 1

The PROPORTION of variance in one variable that is predicted by another variable.

Question 2

What is the least squares technique?

Answer 2

Fitting the regression line based on minimising the sum of squared residuals.

Question 3

How do you calculate R squared?

Answer 3

SSregression / SStotal.

Question 4

What is the Sum of Squares regression?

Answer 4

The AMOUNT of variance accounted for by the IV.

Question 5

What values are used to form the regression equation?

Answer 5

Unstandardised B coefficients.

Question 6

What are the 4 assumptions of simple regression?

Answer 6

IV and DV are at least ordinal, IV and DV have a linear relationship, residuals are normally distributed and residuals have homoscedasiticity.

Question 7

Name 2 ways you can check if variables have a linear relationship.

Answer 7

Scatterplot of IV against DV and scatterplot of predicted scores against residuals.

Question 8

Name 2 ways you can check for normal distribution of residuals.

Answer 8

Scatterplot of predicted scores against residuals and normality plot of residuals.

Question 9

Name 1 way you can check for homoscedasiticity of residuals.

Answer 9

Scatterplot of predicted scores against residuals.

Question 10

What is homoscedasticity of residuals?

Answer 10

When variance of residuals around the regression line is constant for all values of the IV.