Chapter 14

Question 1

ANOVA Table

Answer 1

The analysis of variance table used to summarize the computations associated with the F test for significance.

Question 2

Coefficient of Determination

Answer 2

A measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.

Question 3

Confidence Interval

Answer 3

The interval estimate of the mean value of y for a given value of x.

Question 4

Correlation Coefficient

Answer 4

A measure of the strength of the linear relationship between two variables (previously discussed in Chapter 3).

Question 5

Dependent Variable

Answer 5

The variable that is being predicted or explained. It is denoted by y.

Question 6

Estimated Regression Equation

Answer 6

The estimate of the regression equation developed from sample data by using the least squares method. For simple linear regression, the estimated regression equation is ÿ = bo + b1%.

Question 7

High Leverage Points

Answer 7

Observations with extreme values for the independent variables.

Question 8

Independent Variable

Answer 8

The variable that is doing the predicting or explaining. It is denoted by x.

Question 9

Influential Observation

Answer 9

An observation that has a strong influence or effect on the regression results.

Question 10

ith residual

Answer 10

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation; for the ith observation the th residual is Yi - Y;.

Question 11

Least Squares Method

Answer 11

A procedure used to develop the estimated regression equation. The objective is to minimize

Question 12

Mean Square Error

Answer 12

The unbiased estimate of the variance of the error term σ^2. It is denoted by MSE or s^2

Question 13

Normal Probability Plot

Answer 13

A graph of the standardized residuals plotted against values of the normal scores. This plot helps determine whether the assumption that the error term has a normal probability distribution appears to be valid.

Question 14

Outlier

Answer 14

A data point or observation that does not fit the trend shown by the remaining data.

Question 15

Prediction Interval

Answer 15

The interval estimate of an individual value of y for a given value of x.

Question 16

Regression Equation

Answer 16

The equation that describes how the mean or expected value of the dependent variable is related to the independent variable; in simple linear regression, .

Question 17

Regression Model

Answer 17

The equation that describes how y is related to x and an error term; in simple linear regression, the regression model is

Question 18

Residual Analysis

Answer 18

The analysis of the residuals used to determine whether the assumptions made about the regression model appear to be valid. Residual analysis is also used to identify outliers and influential observations.

Question 19

Residual Plot

Answer 19

Graphical representation of the residuals that can be used to determine whether the assumptions made about the regression model appear to be valid.

Question 20

Scatter Diagram

Answer 20

A graph of bivariate data in which the independent variable is on the horizontal axis and the dependent variable is on the vertical axis.

Question 21

Simple linear Regression

Answer 21

Regression analysis involving one independent variable and one dependent variable in which the relationship between the variables is approximated by a straight line.

Question 22

Standard Error of the Estimate

Answer 22

The square root of the mean square error, denoted by s. It is the estimate of σ, the standard deviation of the error term E.

Question 23

Standardized Residual

Answer 23

The value obtained by dividing a residual by its standard deviation.