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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

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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

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Solution

The example "Predict the salary offered for a certain job" aligns with the modeling type "Regression". This is because regression models are used to predict a continuous outcome variable (in this case, salary) based on one or more predictor variables (in this case, the job).

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Q.12 Align the example with the modeling type they represent-Predict the number of widgets sold next week1. Classification2. Anomaly detection3. Regression4. Time series forecasting

Pay policies indicate the kinds of behaviour an employer seeks. This is a prediction of _____ labour demand theory.Question 5Answera.efficiency wageb.signallingc.compensating differentialsd.human capitale.reservation wage

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.

Which of the following are the important characteristics that determine the choice of the forecasting model?Answer choicesSelect only one optionREVISITPatterns in the dataVolume of the dataVelocity of the dataVariety of Data

Which of the following is a prediction of human capital theory?Question 11Answera.The value of an individual's skills and abilities is a function of the time and expense required to acquire them.b.Higher wages improve efficiency by attracting workers who will perform better.c.Jobs with negative characteristics require higher pay to attract workers.d.Pay policies signal the kinds of behaviour an employer seeks from employees.e.Job seekers will not accept jobs when pay is below a certain wage.

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