Regression Analysis for Economics: Master the Fundamentals

Question 1

The coefficient of determination (R-squared) is a measure of:

Accepted Answer

The proportion of variation in the dependent variable explained by the independent variables

Answer

The slope of the regression line

Answer

The intercept of the regression line

Answer

The standard error of the regression

Question 2

Which of the following is NOT an estimator for the parameters of a regression model?

Accepted Answer

Median regression

Answer

Ordinary least squares (OLS)

Answer

Generalised least squares (GLS)

Answer

Weighted least squares (WLS)

Question 3

What is the primary purpose of a hypothesis test in regression analysis?

Accepted Answer

To determine whether there is a statistically significant relationship between the independent and dependent variables

Answer

To predict the value of the dependent variable for a given set of independent variables

Answer

To identify the best-fitting model among a set of candidate models

Answer

To estimate the parameters of the regression model

Question 4

What is the key difference between simple and multiple regression models?

Accepted Answer

Simple regression has only one independent variable, while multiple regression has more than one.

Answer

Multiple regression is more accurate than simple regression.

Answer

Simple regression is easier to interpret than multiple regression.

Answer

There is no difference between simple and multiple regression.

Question 5

Which of the following is NOT an assumption of the Gauss-Markov theorem?

Accepted Answer

Heteroscedasticity

Answer

Linearity

Answer

Exogeneity

Answer

Normality

Question 6

What is the purpose of using dummy variables in regression analysis?

Accepted Answer

To represent categorical independent variables

Answer

To include interaction effects

Answer

To improve the accuracy of the model

Answer

To reduce the number of independent variables

Question 7

To test the null hypothesis that the coefficient on a particular regressor is equal to zero, we use the:

Accepted Answer

t-test

Answer

F-test

Answer

Wald test

Answer

Likelihood ratio test

Question 8

Multicollinearity occurs when:

Accepted Answer

Two or more regressors are highly correlated.

Answer

The error term is correlated with one or more of the regressors.

Answer

The sample size is too small.

Answer

The model is misspecified.

Question 9

In the context of multiple regression analysis, what primary purpose does the coefficient of determination (R-squared) serve?

Accepted Answer

Evaluating the regression model's goodness of fit.

Answer

Identifying statistically significant independent variables.

Answer

Predicting the dependent variable's value.

Answer

Calculating the regression line's slope.

Question 10

How should the p-value of a hypothesis test in multiple regression analysis be interpreted?

Accepted Answer

A low p-value signifies statistical significance of the independent variable.

Answer

A low p-value suggests that the null hypothesis is more likely to be true.

Answer

A high p-value implies that the null hypothesis is more likely to be true.

Answer

A high p-value indicates statistical significance of the independent variable.

Question 11

Which diagnostic test is commonly used to detect heteroscedasticity?

Accepted Answer

Breusch-Pagan test.

Answer

White test.

Answer

F-test.

Answer

t-test.

Question 12

In the simple linear regression model, which assumption implies a constant error variance?

Accepted Answer

Homoscedasticity

Answer

Linearity

Answer

Independence

Answer

Normality

Question 13

What is the interpretation of the intercept term in a regression equation?

Accepted Answer

The value of the dependent variable when all independent variables are zero.

Answer

The slope of the regression line.

Answer

The average value of the error term.

Answer

The predicted value of the dependent variable.

Question 14

Which estimation method in regression analysis aims to minimize the sum of squared residuals?

Accepted Answer

Ordinary least squares (OLS)

Answer

Weighted least squares (WLS)

Answer

Generalized least squares (GLS)

Answer

Instrumental variable (IV)

Question 15

The coefficient of determination (R-squared) in regression analysis measures:

Accepted Answer

The proportion of variation in the dependent variable explained by the independent variables.

Answer

The accuracy of the model's predictions.

Answer

The significance of the independent variables.

Answer

The presence of outliers.

Question 16

What is the primary purpose of hypothesis testing in regression analysis?

Accepted Answer

To assess the statistical significance of the independent variables.

Answer

To estimate the coefficients of the independent variables.

Answer

To predict the dependent variable.

Answer

To identify outliers.

Question 17

Which source of bias in regression analysis arises when relevant variables are excluded from the model?

Accepted Answer

Omitted variable bias

Answer

Measurement error bias

Answer

Sample selection bias

Answer

Outlier bias

Question 18

What is the main purpose of a Chow test in regression analysis?

Accepted Answer

To test for the equality of coefficients across different samples or groups.

Answer

To test for the presence of autocorrelation in the residuals.

Answer

To test for the significance of the independent variables.

Answer

To identify influential observations.

Question 19

What is the primary purpose of the coefficient of determination (R-squared) in regression analysis?

Accepted Answer

To measure the proportion of variance in the dependent variable explained by the independent variable(s)

Answer

To determine the significance of the regression model

Answer

To predict the value of the dependent variable for a given value of the independent variable

Answer

To test for autocorrelation between errors

Question 20

What is the main purpose of conducting a hypothesis test in regression analysis?

Accepted Answer

To determine whether the overall regression model is statistically significant

Answer

To estimate the parameters of the regression model

Answer

To predict the value of the dependent variable for a given value of the independent variable

Answer

To test for autocorrelation between errors

Question 21

What does the slope coefficient in a regression model represent?

Accepted Answer

The change in the dependent variable for a one-unit increase in the independent variable, holding other variables constant

Answer

The value of the dependent variable when the independent variable is zero

Answer

The proportion of variance in the dependent variable explained by the independent variable

Answer

The significance of the independent variable in the model

Question 22

What is the primary objective of stepwise regression?

Accepted Answer

To select the best subset of independent variables to include in a regression model based on statistical criteria

Answer

To estimate the parameters of a regression model

Answer

To test for autocorrelation between errors

Answer

To diagnose problems with a regression model

Question 23

Which estimation technique is used to find the parameters of a regression model that minimizes the sum of squared residuals?

Accepted Answer

Ordinary least squares (OLS)

Answer

Weighted least squares (WLS)

Answer

Generalized least squares (GLS)

Answer

Maximum likelihood estimation (MLE)

Question 24

What is the purpose of the F-test in regression analysis?

Accepted Answer

To test the overall significance of the regression model.

Answer

To test the significance of individual regression coefficients.

Answer

To test the normality of the error term.

Answer

To test the homoscedasticity of the error term.

Question 25

Which of the following is an assumption of the classical linear regression model?

Accepted Answer

The error term is homoskedastic.

Answer

The regressors are perfectly collinear.

Answer

The error term is uniformly distributed.

Answer

The relationship between the dependent variable and the regressors is non-linear.

Question 26

In a simple regression model, the slope coefficient represents:

Accepted Answer

The change in the dependent variable for a one-unit change in the independent variable, holding other variables constant.

Answer

The correlation between the dependent variable and the independent variable.

Answer

The value of the dependent variable when the independent variable is zero.

Question 27

The coefficient of determination (R-squared) measures:

Accepted Answer

The proportion of the variation in the dependent variable that is explained by the independent variables.

Answer

The significance of the regression model.

Answer

The correlation between the dependent variable and the independent variables.

Question 28

Which of the following hypothesis tests is used to determine if the relationship between two variables is statistically significant?

Accepted Answer

t-test

Answer

ANOVA

Answer

Chi-square test

Answer

F-test

Question 29

What is the purpose of a residual plot?

Accepted Answer

To detect outliers and patterns in the residuals.

Answer

To perform a hypothesis test on the intercept.

Answer

To determine the significance of the regression model.

Answer

To calculate the coefficient of determination.

Question 30

What is the purpose of using a scatterplot to analyze data?

Accepted Answer

To identify patterns and relationships between variables.

Answer

To calculate the mean and standard deviation of the data.

Answer

To test hypotheses about the data.

Question 31

Which of the following is a condition for the Gauss-Markov theorem?

Accepted Answer

The error terms are uncorrelated.

Answer

The predictor variables are highly correlated.

Answer

The error term is heteroskedastic.

Question 32

In a multiple regression model, what is the purpose of the intercept term?

Accepted Answer

To estimate the value of the dependent variable when all predictor variables are equal to zero.

Answer

To indicate the strength of the relationship between the variables.

Answer

To adjust for the slope of the regression line.

Question 33

In hypothesis testing for regression analysis, what is the null hypothesis for testing the significance of a regression coefficient?

Accepted Answer

The coefficient is equal to zero.

Answer

The coefficient is not equal to zero.

Answer

The coefficient is less than zero.

Answer

The coefficient is greater than zero.

Question 34

What is the purpose of a dummy variable in regression analysis?

Accepted Answer

To represent a categorical variable.

Answer

To control for the effect of an omitted variable.

Answer

To improve the goodness-of-fit of the model.

Answer

To test for the presence of heteroscedasticity.

Question 35

What is the difference between simple and multiple regression?

Accepted Answer

Simple regression uses only one predictor variable, while multiple regression uses two or more.

Answer

Simple regression is used for prediction, while multiple regression is used for explanation.

Answer

Simple regression is linear, while multiple regression is non-linear.

Question 36

In a multiple regression model, the coefficient of determination (R-squared) measures:

Accepted Answer

The proportion of variance in the dependent variable explained by the independent variables.

Answer

The intercept of the regression line.

Answer

The number of independent variables.

Question 37

In a hypothesis test for the slope coefficient in a simple linear regression model, the null hypothesis states that:

Accepted Answer

The slope coefficient is equal to zero.

Answer

The slope coefficient is not equal to zero.

Answer

The slope coefficient is greater than zero.

Answer

The slope coefficient is less than zero.

Question 38

Which of the following issues arises in regression analysis when two or more independent variables are highly correlated?

Accepted Answer

Multicollinearity

Answer

Autocorrelation

Answer

Heteroscedasticity

Question 39

In a regression model, the standard error of the estimate measures:

Accepted Answer

The average distance between the actual values of the dependent variable and the predicted values.

Answer

The intercept of the regression line.

Answer

The slope of the regression line.

Question 40

Which of the following types of residual plots is used to assess the assumption of normality?

Accepted Answer

Normal probability plot

Answer

Histogram of residuals

Answer

Scatterplot of residuals against fitted values

Question 41

In multiple regression, the adjusted R-squared statistic takes into account:

Accepted Answer

The number of independent variables in the model.

Answer

The presence of outliers.

Answer

The distribution of the residuals.

Answer

The sample size.

Question 42

In a logarithmic regression model, what transformation is applied to the dependent variable?

Accepted Answer

Natural logarithm

Answer

Inverse

Answer

Exponential function

Answer

Square root