Question 1

What does a simple linear regression analysis examine?

Accepted Answer

A)  The relationship between only two variables 
B)  The relationship between one dependent and one independent variable 
C)  The relationship between many variables 
D)  The relationship between two dependent and one independent variable 
A)  The relationship between only two variables 
B)  The relationship between one dependent and one independent variable 
C)  The relationship between many variables 
D)  The relationship between two dependent and one independent variable A,C

Question 2

Which of the following measures is optimal for comparing the goodness of the fit of competing regression models involving the same dependent variable?

Accepted Answer

A)  The intercept 
B)  The coefficient 
C)  R-square 
D)  Standard deviation of the residuals 
A)  The intercept 
B)  The coefficient 
C)  R-square 
D)  Standard deviation of the residuals D

Question 3

What does the following expression(H₀:₁=0) mean?

Accepted Answer

A)  Mean-Y changes as a result of a change in X 
B)  Mean-Y does not change as a result of change in X 
C)  Mean-Y value becomes 0 as a result of a change in X 
D)  Mean-Y value is equal to 0 when X=0 
A)  Mean-Y changes as a result of a change in X 
B)  Mean-Y does not change as a result of change in X 
C)  Mean-Y value becomes 0 as a result of a change in X 
D)  Mean-Y value is equal to 0 when X=0 B

Question 4

Which of the following are correct?

Accepted Answer

A)  The intercept/constant (β₀) is the mean-Y when X=0 
B)  The intercept is the amount of change in mean-Y when X=0 
C)  The coefficient is the mean-Y at a certain value of X 
D)  The coefficient (β) is the amount of change in mean-Y for every unit increase in X 
A)  The intercept/constant (β₀) is the mean-Y when X=0 
B)  The intercept is the amount of change in mean-Y when X=0 
C)  The coefficient is the mean-Y at a certain value of X 
D)  The coefficient (β) is the amount of change in mean-Y for every unit increase in X

Question 5

What does the least squares method do exactly?

Accepted Answer

A)  Minimizes the distance between data points 
B)  Finds the least problematic regression line 
C)  Finds those (best) values of the intercept and slope that provide us with the smallest value of the residual sum of squares 
D)  Finds those (best) values of the intercept and slope that provide us with the smallest value of the sum of residuals 
A)  Minimizes the distance between data points 
B)  Finds the least problematic regression line 
C)  Finds those (best) values of the intercept and slope that provide us with the smallest value of the residual sum of squares 
D)  Finds those (best) values of the intercept and slope that provide us with the smallest value of the sum of residuals

What does a simple linear regression analysis examine?

Which of the following measures is optimal for comparing the goodness of the fit of competing regression models involving the same dependent variable?

What does the following expression(H₀:₁=0) mean?

Which of the following are correct?

What does the least squares method do exactly?

Research and Statistics

Introduction to STATA

Multiple Regression

Dummy-Variable Regression

Interaction/Moderation Effects Using Regression

Linear Regression Assumptions and Diagnostics

Logistic Regression

Survival Analysis

Multilevel Analysis

Panel Data Analysis

Time-Series Analysis

Exploratory Factor Analysis

Structural Equation Modelling and Confirmatory Factor Analysis

Advanced Statistical Techniques

Programming and Dynamic Reporting Using STATA

Filters

Exam 3: Simple Bivariate Regression

What does a simple linear regression analysis examine?

Which of the following measures is optimal for comparing the goodness of the fit of competing regression models involving the same dependent variable?

What does the following expression(H₀:₁=0) mean?

Which of the following are correct?

What does the least squares method do exactly?

Research and Statistics

Introduction to STATA

Multiple Regression

Dummy-Variable Regression

Interaction/Moderation Effects Using Regression

Linear Regression Assumptions and Diagnostics

Logistic Regression

Survival Analysis

Multilevel Analysis

Panel Data Analysis

Time-Series Analysis

Exploratory Factor Analysis

Structural Equation Modelling and Confirmatory Factor Analysis

Advanced Statistical Techniques

Programming and Dynamic Reporting Using STATA

Filters