Lecture 3

Question 1

Regression analysis:

Answer 1

Investigates the influence of 1 or more independent variables (X: qualitativeór
continuous) on 1 dependent variable (Y: continuous)

1 independent variable: bivariate regression analysis
2 or more independent variables: multiple regression analysis

Question 2

Similarity

Answer 2

echniques assume that the relationship between variables is linear

Question 3

Implication of assumption of linearity:

Answer 3

Scores of dependent variable Y can
be predicted as a linear function of the scores of X with the following form

Question 4

How is the regression line determined?

Answer 4

Regression line: best fitting straight line through the scatter plot
That straight line thatbest fits your scatter plot
That straight line, thatcan predict Organizational Commitment (Y) best
That straight line, for which the error that we make in predicting
OrganizationalCommitment (Y) is as small as possible

Question 5

Ordinary Least Squares

Question 6

Formula for the regression coefficient b:

Question 7

Formula for the intercept/constant:

Question 8

Sums of Squares

Question 9

Proportion explained variance (Effect size)

Question 10

Standard Error of the Estimate

Answer 10

Standard Error of the Estimate is the standard deviation of the residuals
Provides information on typical size of prediction errors (average distance
of datapoints to the regression line, measured in units of Y)
We prefer to have them as ……as possible

Question 11

tandardized regression coefficients β

Question 12

Grand mean centering of independent variables