Q: "Suppose you are interested in studying the relationship between education and wage. More specifically, suppose that you believe the relationship to be captured by the following linear regression model, Wage = Beta0 + Beta1 Education + u Suppose further that you estimate the unknown population linear regression model by OLS. What is the difference between Beta1 and Beta1hat ?"

A)"Both, Beta1 and Beta1hat , are OLS estimators of true parameters of the population regression line."

B)"Beta1 is a true population parameter, the slope of the population regression line, while Beta1hat is the OLS estimator of Beta1 ."

C)"Both, Beta1 and Beta1hat , are true parameters of the population regression line"

D) "Beta1hat is a true population parameter, the slope of the population regression line, while Beta1 is the OLS estimator of Beta1hat"

Q: "A professor decides to run an experiment to measure the effect of time pressure on final exam scores. He gives each of the 400 students in his course the same final exam, but some students have 90 minutes to complete the exam while others have 120 minutes. Each student is randomly assigned one of the examination times based on the flip of a coin. Let Yi denote the number of points scored on the exam by the ith student ( 0 less than or equl to Yi less than or equal to 100), let Xi denote the amount of time that the student has to complete the exam (Xi = 90 or 120), and consider the regression model Yi = Beta0 + Beta1 Xi + ui , E(ui) = 0 Which of the following are true about the unobservable ui ? "

A) there is no way to calculate it

B) ui represents factors other than time that influence the student's performance on the exam.

C) ui will be zero for all students because time spent studying is likely the only factor that affects exam performance.

D) All students will necessarily have the same value of ui because they are part of the same population.

Q:"Suppose that a researcher, using wage data on 235 randomly selected male workers and 263 female workers, estimates the OLS regression Wage = 11.769 + 1.993 × Male, Rsq= 0.04, SER= 3.9, with the respective standard errors for the constant and the Male coefficient of (0.2162) and (0.3384). Wage is measured in dollars per hour and Male is a binary variable that is equal to 1 if the person is a male and 0 if the person is a female. What does an Rsq of 0.04 mean ?"

A) "It means using our explanatory variable, we are only able to explain 4% of the variation in the dependant variable"

B) It means that Male only explains 0.04% of why wages are different across people

C) It tells us that 4% of the people in the sample are male

D) It tells us that the error is on average 4%

Q: "In a regression, if the p-value for a coefficient is 0.0834, do you reject the null hypothesis of it being equal to zero at the 5% level? "

A) Yes

B) No

C) "The p-value is not related to a coefficient, but it tells us the goodness of fit of your regression line."

D) The p-value does not matter when it comes to seeing if coefficients are statistically significant