Lesson 10 Flashcards
What is the difference between a correlation and regression?
A correlation focuses on the magnitude and direction of a relationship two variables while a regression uses this relationship to make predictions about the dependent variable.
What are residuals?
Left over scores or errors in the model fit.
What are the 3 assumptions of regressions? Which one is most important*?
- linearity*
- normal residuals/ distribution
- constant variability
When looking at a graph how to you determine normal residuals.
50% of scores fall above and below the line of best fit
What does the adjusted R-squared value tell us?
The percent variance explained by the dependent variable and what % of the DV can predict the outcome.
What is the difference between a simple linear regression and a multiple regression?
Have two or more predictors (independent variables).
Why do we need standardised beta weights?
similar to a post-hoc test in that they are useful in determining the relative importance of each of our predictors (which one has the most weight or influence).
