Question 1

In the equation   is the _____.

Accepted Answer

A) dependent variable 
B) independent variable 
C)  slope parameter 
D)  intercept parameter 
A) dependent variable 
B) independent variable 
C)  slope parameter 
D)  intercept parameter D

Question 2

Simple regression is an analysis of correlation between two variables.​

Accepted Answer

A) True 
 B)False  True

Question 3

In the regression of y on x, the error term exhibits heteroskedasticity if _____.

Accepted Answer

A) it has a constant variance 
B) Var(y|x) is a function of x 
C)  x is a function of y 
D)  y is a function of x 
A) it has a constant variance 
B) Var(y|x) is a function of x 
C)  x is a function of y 
D)  y is a function of x B

Question 4

In the equation   , c denotes consumption and i denotes income. What is the residual for the 5th observation if   =$500 and   =$475?

Accepted Answer

A) $975 
B) $300 
C)  $25 
D)  $50 
A) $975 
B) $300 
C)  $25 
D)  $50

Question 5

A dependent variable is also known as a(n) _____.

Accepted Answer

A) explanatory variable 
B) control variable 
C)  predictor variable 
D)  response variable 
A) explanatory variable 
B) control variable 
C)  predictor variable 
D)  response variable

Question 6

The variance of the slope estimator increases as the error variance decreases.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following is assumed for establishing the unbiasedness of Ordinary Least Square (OLS) estimates?

Accepted Answer

A) The error term has an expected value of 1 given any value of the explanatory variable. 
B) The regression equation is linear in the explained and explanatory variables. 
C)  The sample outcomes on the explanatory variable are all the same value. 
D)  The error term has the same variance given any value of the explanatory variable. 
A) The error term has an expected value of 1 given any value of the explanatory variable. 
B) The regression equation is linear in the explained and explanatory variables. 
C)  The sample outcomes on the explanatory variable are all the same value. 
D)  The error term has the same variance given any value of the explanatory variable.

Question 8

If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?

Accepted Answer

A) 0.73 
B) 0.55 
C)  0.27 
D)  1.2 
A) 0.73 
B) 0.55 
C)  0.27 
D)  1.2

Question 9

If a change in variable x causes a change in variable y, variable x is called the _____.

Accepted Answer

A) dependent variable 
B) explained variable 
C)  explanatory variable 
D)  response variable 
A) dependent variable 
B) explained variable 
C)  explanatory variable 
D)  response variable

Question 10

The explained sum of squares for the regression function,   , is defined as _____.

Accepted Answer

A)    
B)    
C) 
  
D) 
  
A)    
B)    
C) 
  
D)

Question 11

The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.

Accepted Answer

A) True 
 B)False

Question 12

A natural measure of the association between two random variables is the correlation coefficient.

Accepted Answer

A) True 
 B)False

Question 13

What is the estimated value of the slope parameter when the regression equation, y =   0 +   1x1 + u passes through the origin?

Accepted Answer

A)    
B)    
C) 
  
D) 
  
A)    
B)    
C) 
  
D)

Question 14

There are n-1 degrees of freedom in Ordinary Least Square residuals.

Accepted Answer

A) True 
 B)False

Question 15

Consider the following regression model: y =   0 +   1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

Accepted Answer

A) The sum, and therefore the sample average of the OLS residuals, is positive. 
B) The sum of the OLS residuals is negative. 
C)  The sample covariance between the regressors and the OLS residuals is positive. 
D)  The point (
  ) always lies on the OLS regression line. 
A) The sum, and therefore the sample average of the OLS residuals, is positive. 
B) The sum of the OLS residuals is negative. 
C)  The sample covariance between the regressors and the OLS residuals is positive. 
D)  The point (
  ) always lies on the OLS regression line.

Question 16

Which of the following is a nonlinear regression model?

Accepted Answer

A) y =   0 +   1x1/2 + u 
B) log y =   0 +   1log x +u 
C)  y = 1 / (
  0 +
  1x) + u 
D)  y =
  0 +
  1x + u 
A) y =   0 +   1x1/2 + u 
B) log y =   0 +   1log x +u 
C)  y = 1 / (
  0 +
  1x) + u 
D)  y =
  0 +
  1x + u

Question 17

If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?

Accepted Answer

A) 64 
B) 56 
C)  32 
D)  18 
A) 64 
B) 56 
C)  32 
D)  18

Question 18

R2 is the ratio of the explained variation compared to the total variation.

Accepted Answer

A) True 
 B)False

Question 19

The sample correlation between xi and yi is denoted by _____.​

Accepted Answer

A) ​   
B) ​   
C)  ​
  
D)  ​
  
A) ​   
B) ​   
C)  ​
  
D)  ​

Question 20

If xi and yi are positively correlated in the sample then the estimated slope is _____.​

Accepted Answer

A) ​less than zero 
B) ​greater than zero 
C)  ​equal to zero 
D)  ​equal to one 
A) ​less than zero 
B) ​greater than zero 
C)  ​equal to zero 
D)  ​equal to one

In the equation is the _____.

Simple regression is an analysis of correlation between two variables.

In the regression of y on x, the error term exhibits heteroskedasticity if _____.

In the equation , c denotes consumption and i denotes income. What is the residual for the 5^th observation if =$500 and =$475?

A dependent variable is also known as a(n) _____.

The variance of the slope estimator increases as the error variance decreases.

Which of the following is assumed for establishing the unbiasedness of Ordinary Least Square (OLS) estimates?

If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?

If a change in variable x causes a change in variable y, variable x is called the _____.

The explained sum of squares for the regression function, , is defined as _____.

The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.

A natural measure of the association between two random variables is the correlation coefficient.

What is the estimated value of the slope parameter when the regression equation, y = ₀ + ₁x₁ + u passes through the origin?

There are n-1 degrees of freedom in Ordinary Least Square residuals.

Consider the following regression model: y = ₀ + ₁x₁ + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

Which of the following is a nonlinear regression model?

If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?

R² is the ratio of the explained variation compared to the total variation.

The sample correlation between xi and yi is denoted by _____.

If x_i and y_i are positively correlated in the sample then the estimated slope is _____.

The Nature of Econometrics and Economic Data

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 2: The Simple Regression Model

In the equation is the _____.

Simple regression is an analysis of correlation between two variables.​

In the regression of y on x, the error term exhibits heteroskedasticity if _____.

In the equation , c denotes consumption and i denotes income. What is the residual for the 5th observation if =$500 and =$475?

A dependent variable is also known as a(n) _____.

The variance of the slope estimator increases as the error variance decreases.

Which of the following is assumed for establishing the unbiasedness of Ordinary Least Square (OLS) estimates?

If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?

If a change in variable x causes a change in variable y, variable x is called the _____.

The explained sum of squares for the regression function, , is defined as _____.

The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.

A natural measure of the association between two random variables is the correlation coefficient.

What is the estimated value of the slope parameter when the regression equation, y = 0 + 1x1 + u passes through the origin?

There are n-1 degrees of freedom in Ordinary Least Square residuals.

Consider the following regression model: y = 0 + 1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

Which of the following is a nonlinear regression model?

If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?

R2 is the ratio of the explained variation compared to the total variation.

The sample correlation between xi and yi is denoted by _____.​

If xi and yi are positively correlated in the sample then the estimated slope is _____.​

The Nature of Econometrics and Economic Data

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Simple regression is an analysis of correlation between two variables.

In the equation , c denotes consumption and i denotes income. What is the residual for the 5^th observation if =$500 and =$475?

What is the estimated value of the slope parameter when the regression equation, y = ₀ + ₁x₁ + u passes through the origin?

Consider the following regression model: y = ₀ + ₁x₁ + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

R² is the ratio of the explained variation compared to the total variation.

The sample correlation between xi and yi is denoted by _____.

If x_i and y_i are positively correlated in the sample then the estimated slope is _____.