# Tutor profile: Maria H.

## Questions

### Subject: Spanish

Crecì hablando español en casa. Tome un clase de español en la univesidad donde se enseñaba español a los hispanohablentes de heritencia. Ahi saque la nota màs alta posible. A problem: If you were to say "If I had a million dollars, I'd take a trip to Europe," which would be the correct conjugations of had and take?

You would use tuviera and tomarìa. "Si yo tuviera un millòn de dolares, tomarìa un viaje hacia Europa." Tuviera is used because of its subjective conditional tense. You don't have the money, but if you did, this is what you would do. Tomarìa is used (instead of tuviera again) because the second half is no longer setting up the conditional situation. Instead you are describing what would happen in the future if the conditional statement is met.

### Subject: Economics

You have a dataset (n = 300) with the following information for a sample of college students: COFFEE-number of ounces of daily coffee consumption for a given student SLEEP-the student's hours of sleep on a typical weeknight MAJOR--dummy variable equal to 1 for an Econ major, 0 otherwise The sample includes 150 Econ majors and 150 non-Econ majors. The sample distribution of COFFEE conditional on being an Econ major happens to be identical to the sample distribution of COFFEE conditional on being a non-major. Econ majors in the sample average 7 hours of sleep per night, with a range of 6-8 hours. Non-majors get 8 hours of sleep on average but the amount varies widely across students, with a range of 5 hours to 11 hours. You run two separate OLS regression models and estimate the following regression model: Major: sleep_predicted = beta0 + beta1*COFFEE Non-Major: sleep_predicted = alpha0 + alpha1*COFFEE As it turns out beta1 = alpha1. Is the R-squared in the model for Econ majors greater than, equal to, or less than R-squared in the model for non-majors, or is it uncertain?

R-squared (R^2) is the variation in y explained by the variation in x. Since the variation in coffee consumption is the same for both groups, the smaller variation in the y variable (sleep) for Econ majors hints at more precise estimates. R^2 for Econ majors is > than R^2 for non-majors Reason: variation in sleep for Econ majors < than the variation in sleep for non-majors.

### Subject: Econometrics

You have a dataset (n = 300) with the following information for a sample of college students: COFFEE-number of ounces of daily coffee consumption for a given student SLEEP-the student's hours of sleep on a typical weeknight MAJOR--dummy variable equal to 1 for an Econ major, 0 otherwise The sample includes 150 Econ majors and 150 non-Econ majors. The sample distribution of COFFEE conditional on being an Econ major happens to be identical to the sample distribution of COFFEE conditional on being a non-major. Econ majors in the sample average 7 hours of sleep per night, with a range of 6-8 hours. Non-majors get 8 hours of sleep on average but the amount varies widely across students, with a range of 5 hours to 11 hours. You run two separate OLS regression models and estimate the following regression model: Major: sleep_predicted = beta0 + beta1*COFFEE Non-Major: sleep_predicted = alpha0 + alpha1*COFFEE As it turns out beta1 = alpha1. Is beta0 greater than, equal to, or less than alpha0, or is it uncertain?

First rework the equation: (We are not rearranging the equation, rather using Econometric principles used to determine beta0 and alpha0). Constants (beta0/alpha0) in any regression are found using Beta1/Alpha1 and the means of the distributions. Remember that beta0 is the sum of the mean of the y variable (sleep) and the mean of the x variable (coffee consumption) times beta1 (which is the relationship between the two). beta0 = sleep_mean + Beta1*COFFEE_mean alpha0 = sleep_mean + alpha1*COFEE_mean Thus we can plug in the y means given in the problem. beta0 = 7 + beta1COFFEE_mean alpha0 = 8 = alpha1COFFEE_mean We are also told that coffee consumption is identical in its distribution (average coffee consumption of Econ majors is equal to consumption average by non-majors), and that beta1 = alpha1. Such that: beta1COFFEE_mean = alpha1COFFEE is true statement. beta0 of 7 < alpha0 of 8 beta 0 is (less than) < alpha0.

## Contact tutor

needs and Maria will reply soon.