Question 1

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

Accepted Answer

A) constant term. 
B) error term. 
C) residual. 
D) model parameter. 
A) constant term. 
B) error term. 
C) residual. 
D) model parameter.

Question 2

Assessing the regression model on data other than the sample data that was used to generate the model is known as

Accepted Answer

A) approximation. 
B) cross-validation. 
C) graphical validation. 
D) postulation. 
A) approximation. 
B) cross-validation. 
C) graphical validation. 
D) postulation.

Question 3

__________ refers to the degree of correlation among independent variables in a regression model.

Accepted Answer

A) Multicollinearity 
B) Tolerance 
C) Rank 
D) Confidence level 
A) Multicollinearity 
B) Tolerance 
C) Rank 
D) Confidence level

Question 4

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.

Accepted Answer

A) residual 
B) tolerance factor 
C) confidence level 
D) accuracy level 
A) residual 
B) tolerance factor 
C) confidence level 
D) accuracy level

Question 5

__________ is the data set used to build the candidate models.

Accepted Answer

A) Range 
B) Codomain 
C) Validation set 
D) Training set 
A) Range 
B) Codomain 
C) Validation set 
D) Training set

Question 6

The __________ is the range of values of the independent variables in the data used to estimate the regression model.

Accepted Answer

A) confidence interval 
B) codomain 
C) experimental region 
D) validation set 
A) confidence interval 
B) codomain 
C) experimental region 
D) validation set

Question 7

A regression analysis involving one independent variable and one dependent variable is referred to as a

Accepted Answer

A) factor analysis. 
B) time series analysis. 
C) simple linear regression. 
D) data mining. 
A) factor analysis. 
B) time series analysis. 
C) simple linear regression. 
D) data mining.

Question 8

The coefficient of determination

Accepted Answer

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. 
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.

Question 9

A normally distributed error term with a mean of zero would

Accepted Answer

A) have values that are symmetric about the variance. 
B) allow more accurate modeling. 
C) yield biased regression estimates. 
D) be a hyperbolic curve. 
A) have values that are symmetric about the variance. 
B) allow more accurate modeling. 
C) yield biased regression estimates. 
D) be a hyperbolic curve.

Question 10

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?

Accepted Answer

A) 31.89 
B) 19.32 
C) 18.43 
D) 15.32 
A) 31.89 
B) 19.32 
C) 18.43 
D) 15.32

Question 11

__________ is a statistical procedure used to develop an equation showing how two variables are related.

Accepted Answer

A) Regression analysis 
B) Data mining 
C) Time series analysis 
D) Factor analysis 
A) Regression analysis 
B) Data mining 
C) Time series analysis 
D) Factor analysis

Question 12

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

Accepted Answer

A) inductive inference. 
B) deductive inference. 
C) statistical inference. 
D) Bayesian inference. 
A) inductive inference. 
B) deductive inference. 
C) statistical inference. 
D) Bayesian inference.

Question 13

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

Accepted Answer

A) coefficient of determination. 
B) slope of the regression line. 
C) correlation coefficient. 
D) standard error. 
A) coefficient of determination. 
B) slope of the regression line. 
C) correlation coefficient. 
D) standard error.

Question 14

The graph of the simple linear regression equation is a(n)

Accepted Answer

A) ellipse. 
B) hyperbola. 
C) parabola. 
D) straight line. 
A) ellipse. 
B) hyperbola. 
C) parabola. 
D) straight line.

Question 15

__________ is used to test the hypothesis that the values of the regression parameters ß1, ß2, ... ßq are all zero.

Accepted Answer

A) An F test 
B) A t test 
C) The least squares method 
D) Extrapolation 
A) An F test 
B) A t test 
C) The least squares method 
D) Extrapolation

Question 16

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

Accepted Answer

A) a residual. 
B) the coefficient of determination. 
C) a dummy variable. 
D) interaction. 
A) a residual. 
B) the coefficient of determination. 
C) a dummy variable. 
D) interaction.

Question 17

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?

Accepted Answer

A) Multiple regression model 
B) Quadratic regression model 
C) Simple regression model 
D) Least squares regression model 
A) Multiple regression model 
B) Quadratic regression model 
C) Simple regression model 
D) Least squares regression model

Question 18

The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below? ​

Accepted Answer

A) The residuals have an increasing variance as the dependent variable increases. 
B) The model captures the relationship between the variables accurately. 
C) The regression model follows the standard normal probability distribution. 
D) The residual distribution is consistently scattered about zero. 
A) The residuals have an increasing variance as the dependent variable increases. 
B) The model captures the relationship between the variables accurately. 
C) The regression model follows the standard normal probability distribution. 
D) The residual distribution is consistently scattered about zero.

Question 19

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.

Accepted Answer

A) sum of squares due to regression (SSR) 
B) error term 
C) sum of squares due to error (SS
E)  
D) residual 
A) sum of squares due to regression (SSR) 
B) error term 
C) sum of squares due to error (SS
E)  
D) residual

Question 20

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?

Accepted Answer

A) 2.32 
B) 0.43 
C) 0.19 
D) 0.89 
A) 2.32 
B) 0.43 
C) 0.19 
D) 0.89

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

Assessing the regression model on data other than the sample data that was used to generate the model is known as

__________ refers to the degree of correlation among independent variables in a regression model.

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.

__________ is the data set used to build the candidate models.

The __________ is the range of values of the independent variables in the data used to estimate the regression model.

A regression analysis involving one independent variable and one dependent variable is referred to as a

The coefficient of determination

A normally distributed error term with a mean of zero would

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?

__________ is a statistical procedure used to develop an equation showing how two variables are related.

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

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

The graph of the simple linear regression equation is a(n)

__________ is used to test the hypothesis that the values of the regression parameters ß₁, ß2, ... ß_q are all zero.

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

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?

The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below?

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.

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?

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters

Exam 7: Linear Regression

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

Assessing the regression model on data other than the sample data that was used to generate the model is known as

__________ refers to the degree of correlation among independent variables in a regression model.

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.

__________ is the data set used to build the candidate models.

The __________ is the range of values of the independent variables in the data used to estimate the regression model.

A regression analysis involving one independent variable and one dependent variable is referred to as a

The coefficient of determination

A normally distributed error term with a mean of zero would

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?

__________ is a statistical procedure used to develop an equation showing how two variables are related.

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

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

The graph of the simple linear regression equation is a(n)

__________ is used to test the hypothesis that the values of the regression parameters ß1, ß2, ... ßq are all zero.

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

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?

The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below? ​

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.

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?

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters

__________ is used to test the hypothesis that the values of the regression parameters ß₁, ß2, ... ß_q are all zero.

The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below?