Question 1: Concept tested - Probability, Misconceptions - Independent vs dependent events

1. If the probability of rain on any given day is 0.4, what is the probability of rain for three consecutive days? a) 0.064 b) 0.4 c) 0.6 d) 1.2

Answer: a) 0.064

Question 2: Concept tested - Conditional Probability, Misconceptions - Marginal vs conditional probability

1. In a class of 100 students, 60 students are majoring in economics, and 30 students are majoring in statistics. If 20 students are majoring in both, what is the probability that a randomly chosen student is majoring in statistics given they are majoring in economics? a) 1/2 b) 1/3 c) 2/3 d) 3/5

Answer: b) 1/3

Question 3: Concept tested - Sampling distribution, Misconceptions - Population vs sample mean

1. Which of the following best describes the sampling distribution of the sample mean? a) It is always normally distributed b) It is the distribution of all possible sample means c) It is the distribution of the population mean d) It is the distribution of the sample variance

Answer: b) It is the distribution of all possible sample means

Question 4: Concept tested - Confidence interval, Misconceptions - Confidence level vs interval

1. A 95% confidence interval for the mean weight of a population of apples is calculated to be (120, 140). What is the best interpretation of this interval? a) There is a 95% chance that the true mean weight of the apples is between 120 and 140. b) 95% of the apples in the population have a weight between 120 and 140. c) If we repeat the sampling process many times, 95% of the intervals will contain the true mean weight. d) The true mean weight of the apples is definitely between 120 and 140.

Answer: c) If we repeat the sampling process many times, 95% of the intervals will contain the true mean weight.

Question 5: Concept tested - Hypothesis testing, Misconceptions - Type I vs Type II error

1. When conducting a hypothesis test, which of the following best describes a Type I error? a) Accepting the null hypothesis

when it is false b) Accepting the null hypothesis when it is true c) Rejecting the null hypothesis when it is true d) Rejecting the null hypothesis when it is false

Answer: c) Rejecting the null hypothesis when it is true

Question 6: Concept tested - Simple Linear Regression, Misconceptions - Slope vs intercept

1. In a simple linear regression model, what does the slope coefficient represent? a) The average change in the dependent variable for a one-unit change in the independent variable b) The value of the dependent variable when the independent variable is zero c) The correlation between the dependent variable and the independent variable d) The error term in the regression equation

Answer: a) The average change in the dependent variable for a one-unit change in the independent variable

Question 7: Concept tested - Correlation vs Causation, Misconceptions - Correlation implies causation

1. If the correlation coefficient between two variables X and Y is -0.8, this implies: a) X causes Y to decrease b) Y causes X to decrease c) An increase in X is associated with a decrease in Y, but causation is not established d) There is no relationship between X and Y

Answer: c) An increase in X is associated with a decrease in Y, but causation is not established

Question 8: Concept tested - P-value, Misconceptions - Significance level vs statistical significance

1. If a p-value is 0.03 in a hypothesis test, what can be concluded at the 0.05 significance level? a) Fail to reject the null hypothesis b) Reject the null hypothesis c) The probability that the null hypothesis is true is 0.03 d) The result is not statistically significant

Answer: b) Reject the null hypothesis

Question 9: Concept tested - Multicollinearity, Misconceptions - Correlation vs causation

1. Multicollinearity in a multiple regression model refers to: a) A high correlation between the error term and an independent variable b) A high correlation among some or all of the independent variables c) A high correlation between the dependent variable and the independent variables d) A high R-squared value in the regression model

Answer: b) A high correlation among some or all of the independent variables

Question 10: Concept tested - Heteroscedasticity, Misconceptions - Heteroscedasticity vs Homoscedasticity

1. In a regression model, heteroscedasticity refers to: a) Constant variance of the error terms across all levels of the independent variables b) Increasing variance of the error terms as the value of the independent variable increases c) Decreasing variance of the error terms as the value of the independent variable increases d) Both b and c

Answer: d) Both b and c

Question 11: Concept tested - OLS Assumptions, Misconceptions - Error term vs independent variable

1. In Ordinary Least Squares (OLS) regression, which assumption ensures that the error term has a mean of zero? a) Homoscedasticity b) Linearity c) Independence of error terms d) Exogeneity

Answer: d) Exogeneity

Question 12: Concept tested - F-test, Misconceptions - Comparing individual coefficients vs overall model

1. The F-test in a multiple regression is used to test: a) The significance of individual coefficients b) The overall significance of the regression model c) The goodness of fit of the regression model d) The equality of the variances of two or more groups

Answer: b) The overall significance of the regression model

Question 13: Concept tested - Test Statistic, Misconceptions - T-test vs Z-test

1. In a large sample, which test statistic would you use to test the population mean? a) T-test b) Z-test c) F-test d) Chi-square test

Answer: b) Z-test

Question 14: Concept tested - R-squared, Misconceptions - Coefficient of determination vs correlation coefficient

1. What does the R-squared value represent in a regression model? a) The correlation coefficient between the dependent and independent variable b) The proportion of the variance in the dependent variable that is predictable from the independent variable c) The slope of the regression line d) The standard error of the estimate

Answer: b) The proportion of the variance in the dependent variable that is predictable from the independent variable

Question 15: Concept tested - Residuals, Misconceptions - Residuals vs predicted values

1. Residuals in a regression model are defined as: a) The predicted values of the dependent variable b) The observed values minus the predicted values c) The difference between the observed values of the independent variable and the predicted values of the independent variable d) The sum of the squared differences between the observed values and the predicted values

Answer: b) The observed values minus the predicted values

Question 16: Concept tested - Simultaneous Equation Models, Misconceptions - Identification problem vs estimation problem

1. Which of the following is a major issue in estimating a simultaneous equation model? a) Heteroscedasticity b) The identification problem c) Multicollinearity d) Autocorrelation

Answer: b) The identification problem

Question 17: Concept tested - Dummy Variables, Misconceptions - Coding vs interpretation

1. Dummy variables in a regression model are used to: a) Represent qualitative data b) Correct for multicollinearity c) Improve the fit of the regression line d) Correct for autocorrelation

Answer: a) Represent qualitative data

Question 18: Concept tested - Goodness of Fit, Misconceptions - R-squared vs Adjusted R-squared

1. Which measure adjusts the R-squared value for the number of predictors in the model? a) Adjusted R-squared b) Standard error of the regression c) F-statistic d) Durbin-Watson statistic

Answer: a) Adjusted R-squared

Question 19: Concept tested - Autocorrelation, Misconceptions - Serial correlation vs multicollinearity

1. Which test is commonly used to detect autocorrelation in the error terms of a regression model? a) T-test b) F-test c) Durbin-Watson test d) Chi-square test

Answer: c) Durbin-Watson test

Question 20: Concept tested - Instrumental Variables, Misconceptions - Endogeneity vs exogeneity

1. Instrumental variables are used in regression analysis to: a) Correct for multicollinearity b) Correct for autocorrelation c) Correct for endogeneity d) Increase the R-squared value

Answer: c) Correct for endogeneity

Question 21: Concept tested - Probability Distribution, Misconceptions - Mean vs median of a distribution

1. In a symmetric distribution, which of the following is true? a) Mean = Median = Mode b) Mean > Median c) Mean < Median d) Median > Mode

Answer: a) Mean = Median = Mode

Question 22: Concept tested - Maximum Likelihood Estimation, Miscon