Chapter 13 Regression

Question 1

Overpredicted

Answer 1

Observed values of Y at given values of X that are below the predicted values of Y.
( i.e. the, values predicted by the regression equation)

Question 2

Regression Coefficient

Answer 2

A measure of the relationship b/w each predictor varaible and the dependent variable in simple linear regression, this is also the slope of the regression line.
In multiple regression, the variance regression coefficients combine to create the slope of regression line.

Question 3

Intercept

Answer 3

Point in which the regression line intersects the Y axis. Also, the value of Y when X = 0

Question 4

Regression Line

Answer 4

The line that can be drawn through the scatter plot of the data that best “ fits” the data. ( i.e. minimizes the squared deviations b/w observed values and the regression line)

Question 5

Residuals

Answer 5

Errors in prediction. The difference b/w observed and predicted values of Y.

Question 6

Regression Equation

Answer 6

The components, including the regression coefficients intercept, error term, and X and Y values for Y the regression line.

Question 7

Multiple Correlation Coefficient

Answer 7

A statistic measuring the strength of the association b/w multiple independent variables, as a group and dependent variable.

Question 8

Multicollinearity

Answer 8

The degree of overlap among predictor variables in a multiple regression.
High multicollinearity among predictor variables can cause difficulties finding unique relations among predictors and dependant variables.

Question 9

Independent, Predictor Variable

Answer 9

Aka: Independent Variable

Question 10

Dependent, Outcome, Criterion Variable

Answer 10

Different terms for dependent variable

Question 11

Error

Answer 11

Amount of difference b/w the predicted value and the observed value of the dependent variable. It is also the amt. of unexplained variance in a dependent variable,

Question 12

Ordinary Least Squares ( OLS)

Answer 12

A common form of regression that uses the smallest sum of squared deviations to generate the regression line.

Question 13

Observed value

Answer 13

The actual measured value of the Y variable of a given value of X

Question 14

Multiple Regression

Answer 14

A regression model with more than one independent or predictor variable

Question 15

Simple Linear Regression

Answer 15

The regression model employed when their is a single dependent and independent

Question 16

Scatterplot

Answer 16

A graphic representation of the data along 2 dimensions

( x and Y)

Question 17

Standardized Regression Coefficient ( R )

Answer 17

The regression coefficient converted into standardized values.

Question 18

Slope

Answer 18

The average amt. of change in the Y variable for each one unit of change in the X variable.

Question 19

Underpredicted

Answer 19

Observed values of Y at given values of X that are above the predicted values of Y.
( i.e. the values predicted by the regression equation)

Question 20

Unique Variance

Answer 20

The proportion of variance in the dependent variable explained by a independent variable when controlling for all other independent variables in the model.

Question 21

e

Answer 21

Error Mean

Question 22

R

Answer 22

Multiple Correlation Coefficient

Question 23

R2

Answer 23

The % of variance explained by the regression model

Question 24

b

Answer 24

The Understandardized Regression Coefficient

Question 25

Y

Answer 25

Predicted value of Y. The Dependent Variable

Question 26

Y

Answer 26

Observed Value of Y the Dependent Variable

Question 27

a

Answer 27

Intercept