Regression and Correlation

Question 1

Q: What is the main purpose of correlation analysis?

Answer 1

A: To measure the strength and direction of the relationship between two variables.

Question 2

Q: When should you use regression analysis instead of correlation?

Answer 2

A: When you want to predict or explain the value of a dependent variable using one or more independent variables.

Question 3

Q: What type of variables do correlation and regression use?

Answer 3

A: Both require continuous (scale) variables — though regression can also include dummy-coded categorical predictors.

Question 4

Q: What does Pearson’s r tell you in a correlation analysis?

Answer 4

A: The strength (0 to ±1) and direction (positive/negative) of the linear relationship between two variables.

Question 5

Q: What are the key outputs in a linear regression?

Answer 5

A: The regression equation, Beta coefficients, R² (explained variance), and p-values for significance.

Question 6

Q: How do you run a correlation in SPSS?

Answer 6

A: Go to Analyze > Correlate > Bivariate, select two variables, and look at Pearson’s r and Sig. (2-tailed).

Question 7

Q: How do you run a linear regression in SPSS?

Answer 7

A: Go to Analyze > Regression > Linear, put your dependent variable in “Dependent”, and predictors in “Independent(s)”.

Question 11

Q: What does R² mean in regression analysis?

Answer 11

A: It shows the percentage of variance in the dependent variable that is explained by the predictors.