Problem 2:Using the dataset driving.dta, which is a random sample of high school students in 2001, answer the following questions.:1.Use the desc command to take a look at what the variables are. Note that many are dummy variables. In this data set, the categorical variables have been given value labels. Thus, when you use the codebook command to look at the variables gradecat, it ranges from 1 to 5. If you use the tab command, however, you see that each number represents a category. Look at the means of all the variables. Look at frequencies for the categorical variable and create a set of dummy variables for it.2.Suppose that you are interested in the determinants of seatbelt wearing. You have in mind the following model: seat belt wearing= f(grades, race, sex, whether you have driven drunk, and whether you have rode with a drunk). Estimate the econometric model implied by this model (i.e., create an econometric model with seat belt wearing as the dependent variable and a series of dummy variables as independent variables), assuming that you want your comparison group to be white males who usually get Fs and have driven drunk and rode with a drunk.3. Are blacks significantly more or less likely than whites to wear seatbelts? What about Hispanics? What about people who ride with drunk drivers? What about people who are themselves drunk drivers? Does being a better student make you more or less likely to wear a seatbelt?4. Are males or females more likely to wear seatbelts? If the data set had a dummy for male, instead of for female, what would the estimated coefficient on the male dummy be?5.Create interactions of female and drivedrunk and of female and ridedrunk and add them to the regression. Are the coefficients on these 2 new variables individually significantly different from zero at the 5% level (assuming a 2-sided test)? Among males, what is the effect of riding with a drunk? Among females? What is the derivative of seatbelt wearing with respect to being female?因为DTA文件不可以上传,所以能帮忙的能不能吧指令写下来~~万分感谢,急~