Chapter 20 Regression and Multiple Regression Flashcards Preview

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Flashcards in Chapter 20 Regression and Multiple Regression Deck (15)
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1

b weight

The amount by which a criterion variable will increase for a one-unit increase in a predictor variable; a predictor's coefficient in the multiple regression equation

2

Beta value

Standardised b weights (i.e., as expressed in standard deviations)

3

Collinearity

Extent of correlations between predictor variables

4

Criterion/target/dependent variable

Variable on which values are being predicted in regression

5

Heteroscedascity

Degree to which the variance of residuals is not similar across different values of predicted levels of the criterion

6

Linear regression

Procedure of predicting values on a criterion variable from a predictor or predictors using correlation

7

Multiple correlation coefficient

Value of the correlation between actual values of the criterion variable used in multiple regression and the predicted values

8

Multiple regression

Analysis in which the value of one 'criterion' variable is estimated using its known correlations with several other 'predictor' variables

9

Partial correlation

Method of finding the correlation of A with B after the common variance of a third correlated variable, C, has been removed ('partialled out')

10

Predictor

Variable used in combination with others to predict values of a criterion variable in multiple regression

11

Regression coefficient

Amount by which predictor variable values are multiplied in a regression equation in order to estimate criterion variable values

12

Regression line

Line of best fit on a scatterplot which minimises residuals

13

Residual

Difference between an actual score and what it would be as predicted by a predictor variable or by a set of predictor variables

14

Semi-partial correlation

Correlation between a criterion variable B with the residuals of A, after A has been regressed on C. Removes the common variance of A and C from the correlation of A with B.

15

Standardised regression coefficient

Full name for beta values in multiple regression