Regression

Question 1

What does regression mean?

Answer 1

-How does variable X predict variable Y
-Can have multiple regression where many variables/predictors affect something

Question 2

What can regression be used for?

Answer 2

-To make a simple prediction

Question 3

What are IV’s referred to as?

Answer 3

-Predictor variables

Question 4

What are DV’s referred to as?

Answer 4

-Outcome/criterion variables

Question 5

The strength of predictors is shown by…

Answer 5

-Beta values
-Positive beta = positive predictor
-Negative beta = negative predictor

Question 6

What are the key outputs of regression?

Answer 6

p value – overall model fit.
i.e., Is using your model better than using the observed outcome variable mean?

r2 – Goodness of fit.
i.e., how much of your outcome variable variance is explained by your predictors?

β – unstandardised beta.
i.e., What’s the direction and strength of the relationship?

b – standarsised beta.
i.e., if multiple predictors, how do they compare?

Question 7

What has to be considered when plotting multiple regression?

Answer 7

-Simple regression - Line of best fit
-Multiple regression - Plane of best fit