ISDS 361B - Ch. 7

What would be the coefficient of determination if the total sum of squares (SST) is 23.29 and the sum of squares due to regression (SSR) is 10.03? a. 0.89 b. 2.32 c. 0.19 d. 0.43

d. 0.43

What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89? a. 19.32 b. 15.32 c. 31.89 d. 18.43

d. 18.43

The _______________ is the range of values of the independent variables in the data used to estimate the regression model. a. confidence interval b. validation set c. codomain d. experimental region

d. experimental region

Regression analysis involving one dependent variable and more than one independent variable is known as a. linear regression. b. simple regression. c. none of these. d. multiple regression.

d. multiple regression.

In a simple linear regression analysis the quantity that gives the amount by which the dependent variable changes for a unit change in the independent variable is called the a. correlation coefficient. b. standard error. c. coefficient of determination. d. slope of the regression line.

d. slope of the regression line.

The scatter chart below displays the residuals verses the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below? ​ (cone shaped graph where residuals are close together on the left and farther away on the right) a. The residuals have a increasing variance as the dependent variable increases. b. The model captures the relationship between the variables accurately. c. The residual distribution is consistently scattered about zero. d. The regression model follows the standard normal probability distribution.

a. The residuals have a increasing variance as the dependent variable increases.

__________ is the data set used to build the candidate models. a. Training set b. Validation set c. Codomain d. Range

a. Training set

In the graph of the simple linear regression equation, the parameter is the ___________ of the regression line. a. y-intercept b. slope c. end-point d. x-intercept

b. slope

The ____________________ is a measure of the error that results from using the estimated regression equation to preduct the values of the dependent variable in the sample a. error term b. sum of squares due to error (SSE) c. sum of squares due to regression (SSR) d. residual

b. sum of squares due to error (SSE)

______________ refers to the degree of correlation among independent variables in a regression model. a. Tolerance b. Confidence level c. Multicollinearity d. Rank

c. Multicollinearity