Lecture 8

Question 1

Regression provides us with the statistical framework for testing a whole range of models, which are?

Answer 1

• linear regression modelling
• least squares linear regression modelling
• regression modelling

Question 2

Regression modelling provides a platform to explore the ____ of ______ among ______.

Answer 2

Pattern; relationships; variables.

Question 3

Simple univariate regression can be used to explain this relationship how?

Answer 3

• simple= one predictor

* univariate= one dependent variable

Question 4

What is the regression equation?

Answer 4

Is the regression equation is a mathematical expression of the line of best fit/ the regression model

Question 5

How to write the regression equation?

Answer 5

Y(predicted) = B (X) + C

Y = predicted values of the outcome 
B= the slope of the line
X = scores on the predictor 
C = the intercept

Question 6

What is the ANOVA testing?

Answer 6

Technically a test of whether that value is greater than zero.

Question 7

What two questions are asked in multiple aggression?

Answer 7

How well does this combination or predictors predict the outcome?
What is the role of each individual predictor in this relationship?

Question 8

What does R equal and the definition?

Answer 8

R = multiple R: the correlation between the actual scores on the DV and the scores predicted by the aggression equation.

Question 9

Define R^2?

Answer 9

The proportion of variance in the DV that is accounted for by the combined predictors.

Question 10

Define the beta weights?

Answer 10

The standardised regression coefficients. Allows you to directly compare regressions soefficients.

Question 11

What t scores?

Answer 11

Tests the significance of the unique contribution of each predictor.

Question 12

What’s part^2?

Answer 12

The squared semi-partial correlation. Describes the unique relationship between each predictor and the DV in that model.