Chapter 7

A procedure for using sample data to find the estimated regression equation is a. point estimation. b. interval estimation. c. the least squares method. d. extrapolation.

c

The graph of the simple linear regression equation is a(n) a. ellipse. b. hyperbola. c. parabola. d. straight line.

d

In a linear regression model, the variable that is being predicted or explained is known as _____________. It is denoted by y and is often referred to as the response variable. a. dependent variable b. independent variable c. residual variable d. regression variable

a

In the graph of the simple linear regression equation, the parameter ß1 is the ___________ of the true regression line. a. slope b. x-intercept c. y-intercept d. end-point

a

The degree of correlation among independent variables in a regression model is called a. multicollinearity. b. interaction. c. the coefficient of determination. d. the sum of squared errors (SSE).

a

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

a

__________ refers to the scenario in which the relationship between the dependent variable and one independent variable is different at different values of a second independent variable. a. Interaction b. Multicollinearity c. Autocorrelation d. Covariance

a

The population parameters that describe the y-intercept and slope of the line relating y and x, respectively, are a. B0 and B1. b. y and x. c. a and b. d. a and B.

a

_________ refers to the use of sample data to calculate a range of values that is believed to include the value of the population parameter. a. Interval estimation b. Hypothesis testing c. Statistical inference d. Point estimation

a

__________ is a statistical procedure used to develop an equation showing how two variables are related. a. Regression analysis b. Data mining c. Time series analysis d. Factor analysis

a

__________ is used to test the hypothesis that the values of the regression parameters ß1, ß2, ... ßq are all zero. a. An F test b. A t test c. The least squares method d. Extrapolation

a

. In a simple linear regression model, y = ß0 + ß1x + ε the parameter ß1 represents the a. intercept. b. slope of the true regression line. c. mean value of x. d. error term.

b

A __________ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables. a. contingency table b. scatter chart c. Gantt chart d. pie chart

b

A normally distributed error term with a mean of zero would a. have values that are symmetric about the variance. b. allow more accurate modeling. c. yield biased regression estimates. d. be a hyperbolic curve.

b

Assessing the regression model on data other than the sample data that was used to generate the model is known as a. approximation. b. cross-validation. c. graphical validation. d. postulation.

b

In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the __________. It(they) is(are) denoted by x. a. dependent variable b. independent variable c. residual variable d. regression variable

b

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. coefficient of determination. b. slope of the regression line. c. correlation coefficient. d. standard error.

b

In the simple linear regression model, the ____________ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between the variables. a. constant term b. error term c. model parameter d. residual

b

The ___________ is 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. a. residual b. coefficient of determination c. dummy variable d. interaction variable

b

The prespecified value of the independent variable at which its relationship with the dependent variable changes in a piecewise linear regression model is referred to as the a. milestone. b. knot. c. tipping point. d. watchpoint.

b

The process of making a conjecture about the value of a population parameter, collecting sample data that can be used to assess this conjecture, measuring the strength of the evidence against the conjecture that is provided by the sample, and using these results to draw a conclusion about the conjecture is known as a. postulation. b. hypothesis testing. c. statistical inference. d. empirical research.

b

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. 2.32 b. 0.43 c. 0.19 d. 0.89

b

When the mean value of the dependent variable is independent of variation in the independent variable, the slope of the regression line is a. positive. b. zero. c. negative. d. infinite.

b

Which of the following regression models is used to model a nonlinear relationship between the independent and dependent variables by including the independent variable and the square of the independent variable in the model? a. Multiple regression model b. Quadratic regression model c. Simple regression model d. Least squares regression model

b

A regression analysis involving one independent variable and one dependent variable is referred to as a a. factor analysis. b. time series analysis. c. simple linear regression. d. data mining.

c

A variable used to model the effect of categorical independent variables in a regression model is known as a a. dependent variable. b. response. c. dummy variable. d. predictor variable.

c

A variable used to model the effect of categorical independent variables in a regression model which generally takes only the value zero or one is called a. a residual. b. the coefficient of determination. c. a dummy variable. d. interaction.

c

Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as a. approximation. b. hypothesizing. c. overfitting. d. postulating.

c

In the graph of the simple linear regression equation, the parameter ß0 represents the ___________ of the true regression line. a. slope b. x-intercept c. y-intercept d. end-point

c

Prediction of the mean value of the dependent variable y for values of the independent variables x1, x2, . . . , xq that are outside the experimental range is called a. dummy variable. b. overfitting. c. extrapolation. d. interaction.

c

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

c

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. 31.89 b. 19.32 c. 18.43 d. 15.32

c

__________ refers to the data set used to compare model forecasts and ultimately pick a model for predicting values of the dependent variable. a. Codomain b. Training set c. Validation set d. Range

c

Prediction of the value of the dependent variable outside the experimental region is called a. interpolation. b. forecasting. c. averaging. d. extrapolation.

d

The coefficient of determination a. takes values between -1 to +1. b. is equal to zero for a perfect fit. c. is equal to negative one for the poorest fit. d. is used to evaluate the goodness of fit.

d

The least squares regression line minimizes the sum of the a. differences between actual and predicted y values. b. absolute deviations between actual and predicted y values. c. absolute deviations between actual and predicted x values. d. squared differences between actual and predicted y values.

d

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

d

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

c

The __________ is an indication of how frequently interval estimates based on samples of the same size taken from the same population using identical sampling techniques will contain the true value of the parameter we are estimating. a. residual b. tolerance factor c. confidence level d. accuracy level

c

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

c

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the a. constant term. b. error term. c. residual. d. model parameter.

c

The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as a. inductive inference. b. deductive inference. c. statistical inference. d. Bayesian inference.

c