Question

Statistics Question: (look at PNG) Suppose a movie studio has surveyed 1,000 random 18-22 year olds to see if they’ve watched their latest movie, and they wish to estimate the following regression model using OLS: Where if person i has watched the movie (and = 0 otherwise), if person i was a student (and = 0 otherwise), and is the natural log of person i's parents' income. The OLS estimate of the parameter will tell us... Group of answer choices The percent of students who watched the movie. The likelihood of a non-student having watched the movie. The difference in the likelihood of watching the movie between a student and a non-student, controlling for parental income. The likelihood of a non-student with parent’s income of $0 having watched the movie.

Answer 1

The OLS estimate of the parameter in this regression model will tell us the difference in the likelihood of watching the movie between a student and a non-student, controlling for parental income.

In the given regression model, we have three variables: whether a person has watched the movie, whether they are a student, and the natural log of their parents' income. The OLS estimate of the parameter will help us understand the relationship between these variables and the likelihood of watching the movie.

By estimating the regression model using OLS (Ordinary Least Squares), we can determine the impact of being a student on the likelihood of watching the movie, while also controlling for parental income. The parameter estimate will provide us with a quantitative measure of the difference in the likelihood of watching the movie between students and non-students, considering the effect of parental income.

It's important to note that the OLS estimate will not directly give us the percent of students who watched the movie or the likelihood of a non-student having watched the movie. The estimate is specific to the relationship between being a student/non-student and the likelihood of watching the movie, accounting for parental income as well.