Questions 1-4 are based on the following scenario:700 income-earning individuals from a district were randomly selected and asked whether they were employed by the government (Gov = 1) or failed their entrance test (Gov = 0); data were also collected on their gender (Male = 1) if male and = 0 if female) and their years of schooling (Schooling, in years). The following table summarizes several estimated models. (Standard errors are in parentheses).Choose the correct statement: a. The large difference between the estimates in column (1) and the ones in column (2) implies that predicted probabilities would be highly sensitive to whether the Logit model is employed or the Probit model is employed. b. Column (1) suggests that the government would hire a job candidate with 16 years of education with 24.5% probability, i.e., 0.245 = 0.272 X 16 - 4.107. c. Column (2) suggests that the government would hire a job candidate with 16 years of education with 67.0% probability, i.e., 0.670 = 0.551 X 16 - 8.146. d. Column (3) suggests that the government would hire a job candidate with 16 years of education with 38.8% probability, i.e., 0.388 = 0.035 X 16 - 0.172. e. Column (4) suggests that the government would not hire anyone because the estimated coefficients are all negative.

Continue to use the information from Question 1.Choose the correct statement about column (7): a. The coefficients are estimated by the usual OLS method. b. A drawback of the model is that a predicted probability can be larger than 1. c. The Probit model is easier to compute than the Logit mode when an interaction term is included. d. The estimates suggest that the Government would be more likely to hire a woman than a man if both candidates have 16 years of schooling, but the Government would be more likely to hire a man than a woman if both candidates have 12 years of schooling. e. The estimates suggest that the Government would hire a job candidate with a probability larger than 10% regardless of the gender.

Q.11 Align the example with the modeling type they represent-Predict the salary offered for a certain job1. Classification2. Anomaly detection3. Regression4. Time series forecasting

The question below consists of a question and two statements numbered I and II given below it. You have to decide whether the data provided in the statements are sufficient to answer the questions. Read both the statements and give an answer.In a class of 30 students, Angela secured the third rank among the girls, while her brother Reagan studying in the same class secured the sixth rank in the whole class. Between the two, who had the lowest overall rank? I. Reagan was among the top 25% of the boys' merit list in the class of which 60% were boys. II. There were three boys among the top five rank holders and three girls among the top ten rank holders.

This exercise refers to the drunk driving panel data regression, summarised in Table 10.1 on pages 31 and 32 of the Lecture 8 slides.Suppose you are interpreting the estimated coefficient on Real Income Per Capita (Income) as the causal effect on Traffic Fatality Rate. Choose the correct statement: a. According to column (3), the true model must not include Income in the analysis. b. According to column (4), when Income increases by $1, the number of fatalities would increase by 1.82 deaths per 10,000 but the prediction is not statistically significant. c. According to column (5), when Income increases by $1, the number of fatalities would increase by 0.09 deaths per 10,000 but the prediction is not statistically significant. d. According to column (6), when Income increases by 1 percent, the number of fatalities would increase by 0.0179 deaths per 10,000 and the prediction is statistically significant. e. According to column (7), when Income increases by 1 percent, the number of fatalities would increase by 0.01 deaths per 10,000 and the prediction is statistically significant.

Human capital theory suggests that those who have invested in higher levels of education will be able to command higher wages. A labour economist collected data on annual wages (Y, in $'000) and years of study (X) from a random sample of 12 employees to test this proposition. Assuming a linear relationship between Y and X, the labour economist used a least-squares method and found that the Y intercept = -23.50 and the slope = 9.73. The labour economist also found that the standard error of the slope was 1.61. Based on this information, what statistical decision would you made if you are testing the null hypothesis that there is no linear relationship between the two variables, X and Y? a. Accept the null hypothesis. b. Reject the null hypothesis. c. Do not reject the null hypothesis. d. Reject the alternative hypothesis.