Question 1

In a simple linear regression problem,suppose that   = 12.48 and   = 124.8.Then the percentage of variation explained   must be 0.90.

Accepted Answer

A) True 
 B)False

Question 2

The regression line   has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be:

Accepted Answer

A) 20.25 
B) 16.00 
C) 49.00 
D) 94.25 
A) 20.25 
B) 16.00 
C) 49.00 
D) 94.25

Question 3

A useful graph in almost any regression analysis is a scatterplot of residuals (on the vertical axis)versus fitted values (on the horizontal axis),where a "good" fit not only has small residuals,but it has residuals scattered randomly around zero with no apparent pattern.

Accepted Answer

A) True 
 B)False

Question 4

A constant elasticity,or multiplicative,model the dependent variable is expressed as a product of explanatory variables raised to powers

Accepted Answer

A) True 
 B)False

Question 5

In every regression study there is a single variable that we are trying to explain or predict.This is called the response variable or dependent variable.

Accepted Answer

A) True 
 B)False

Question 6

In a multiple regression problem with two explanatory variables if,the fitted regression equation is   ,then the estimated value of Y when   and   is 49.4.

Accepted Answer

A) True 
 B)False

Question 7

The percentage of variation (   )can be interpreted as the fraction (or percent)of variation of the

Accepted Answer

A) explanatory variable explained by the independent variable 
B) explanatory variable explained by the regression line 
C) response variable explained by the regression line 
D) error explained by the regression line 
A) explanatory variable explained by the independent variable 
B) explanatory variable explained by the regression line 
C) response variable explained by the regression line 
D) error explained by the regression line

Question 8

In the multiple regression model   we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

Accepted Answer

A) True 
 B)False

Question 9

Regression analysis can be applied equally well to cross-sectional and time series data.

Accepted Answer

A) True 
 B)False

Question 10

The adjusted R2 is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model

Accepted Answer

A) True 
 B)False

Question 11

The percentage of variation (R2)ranges from

Accepted Answer

A) 0 to +1 
B) -1 to +1 
C) -2 to +2 
D) -1 to 0 
A) 0 to +1 
B) -1 to +1 
C) -2 to +2 
D) -1 to 0

Question 12

In regression analysis,we can often use the standard error of estimate   to judge which of several potential regression equations is the most useful.

Accepted Answer

A) True 
 B)False

Question 13

Approximately what percentage of the observed Y values are within on standard error of the estimate (   )of the corresponding fitted Y values?

Accepted Answer

A) 67% 
B) 95% 
C) 99% 
D) It is not possible to say 
A) 67% 
B) 95% 
C) 99% 
D) It is not possible to say

Question 14

A scatterplot that appears as a shapeless mass of data points indicates:

Accepted Answer

A) a curved relationship among the variables 
B) a linear relationship among the variables 
C) a nonlinear relationship among the variables 
D) no relationship among the variables 
A) a curved relationship among the variables 
B) a linear relationship among the variables 
C) a nonlinear relationship among the variables 
D) no relationship among the variables

Question 15

Given the least squares regression line,

Accepted Answer

A) the relationship between X and Y is positive 
B) the relationship between X and Y is negative 
C) as X increases,so does Y 
D) as X decreases,so does Y 
E) there is no relationship between X and Y 
A) the relationship between X and Y is positive 
B) the relationship between X and Y is negative 
C) as X increases,so does Y 
D) as X decreases,so does Y 
E) there is no relationship between X and Y

Question 16

If a categorical variable is to be included in a multiple regression,a dummy variable for each category of the variable should be used,but the original categorical variables should not be sued.

Accepted Answer

A) True 
 B)False

Question 17

is/are especially helpful in identifying outliers.

Accepted Answer

A) Linear regression 
B) Regression analysis 
C) Normal curves 
D) Scatterplots 
E) Multiple regression 
A) Linear regression 
B) Regression analysis 
C) Normal curves 
D) Scatterplots 
E) Multiple regression

In a simple linear regression problem,suppose that = 12.48 and = 124.8.Then the percentage of variation explained must be 0.90.

The regression line has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be:

A useful graph in almost any regression analysis is a scatterplot of residuals (on the vertical axis)versus fitted values (on the horizontal axis),where a "good" fit not only has small residuals,but it has residuals scattered randomly around zero with no apparent pattern.

A constant elasticity,or multiplicative,model the dependent variable is expressed as a product of explanatory variables raised to powers

In every regression study there is a single variable that we are trying to explain or predict.This is called the response variable or dependent variable.

In a multiple regression problem with two explanatory variables if,the fitted regression equation is ,then the estimated value of Y when and is 49.4.

The percentage of variation ( $The percentage of variation ( )can be interpreted as the fraction (or percent)of variation of the$ )can be interpreted as the fraction (or percent)of variation of the

In the multiple regression model we interpret X₁ as follows: holding X₂ constant,if X₁increases by 1 unit,then the expected value of Y will increase by 9 units.

Regression analysis can be applied equally well to cross-sectional and time series data.

The adjusted R² is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model

The percentage of variation (R²)ranges from

In regression analysis,we can often use the standard error of estimate to judge which of several potential regression equations is the most useful.

Approximately what percentage of the observed Y values are within on standard error of the estimate ( )of the corresponding fitted Y values?

A scatterplot that appears as a shapeless mass of data points indicates:

Given the least squares regression line,

If a categorical variable is to be included in a multiple regression,a dummy variable for each category of the variable should be used,but the original categorical variables should not be sued.

is/are especially helpful in identifying outliers.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters

Exam 10: Regression Analysis: Estimating Relationships

In a simple linear regression problem,suppose that = 12.48 and = 124.8.Then the percentage of variation explained must be 0.90.

The regression line has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be:

A useful graph in almost any regression analysis is a scatterplot of residuals (on the vertical axis)versus fitted values (on the horizontal axis),where a "good" fit not only has small residuals,but it has residuals scattered randomly around zero with no apparent pattern.

A constant elasticity,or multiplicative,model the dependent variable is expressed as a product of explanatory variables raised to powers

In every regression study there is a single variable that we are trying to explain or predict.This is called the response variable or dependent variable.

In a multiple regression problem with two explanatory variables if,the fitted regression equation is ,then the estimated value of Y when and is 49.4.

The percentage of variation ( )can be interpreted as the fraction (or percent)of variation of the

In the multiple regression model we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

Regression analysis can be applied equally well to cross-sectional and time series data.

The adjusted R2 is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model

The percentage of variation (R2)ranges from

In regression analysis,we can often use the standard error of estimate to judge which of several potential regression equations is the most useful.

Approximately what percentage of the observed Y values are within on standard error of the estimate ( )of the corresponding fitted Y values?

A scatterplot that appears as a shapeless mass of data points indicates:

Given the least squares regression line,

If a categorical variable is to be included in a multiple regression,a dummy variable for each category of the variable should be used,but the original categorical variables should not be sued.

is/are especially helpful in identifying outliers.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters

The percentage of variation ( $The percentage of variation ( )can be interpreted as the fraction (or percent)of variation of the$ )can be interpreted as the fraction (or percent)of variation of the

In the multiple regression model we interpret X₁ as follows: holding X₂ constant,if X₁increases by 1 unit,then the expected value of Y will increase by 9 units.

The adjusted R² is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model

The percentage of variation (R²)ranges from