1 ) Suppose that the population average of (monthly) wage of young employees in Tasmania in the previous year before this survey was conducted was $900.

• Conduct a hypothesis test that the population average wage of young employees in Tasmania during the year of survey remains the same as in the previous year.
• Construct a 95% confidence estimate for the population average wage, and comment whether the population average wage in the year of survey remains the same as in the previous year.

2) You want to use the collected data to study what is the most important factor that affects young employees wage in Tasmania. Use simple regression analysis to answer the following questions. (For each regression you run, show the Excel regression output and report the regression equation. Partial marks from the following questions assign to your regression results.).

• Do the years of education have significant impact on the wages? (You need to explain the choice of the null and the alternative hypotheses.
• Do the IQ scores have significant impact on the wages? (You need to explain the choice of the null and the alternative hypotheses.
• Which of the two variables is a better predictor for the wage, years of education or IQ scores? Explain why?
• Do the years of work experience have significant impact on the wages? (You need to explain the choice of the null and the alternative hypotheses.
• Do the KW scores have significant impact on the wages? (You need to explain the choice of the null and the alternative hypotheses.
• Which of the two variables is a better predictor for the wages, years of work experience or KW scores? Explain why?
• Newspapers often criticize a weak link between wage and education comparing with the link between wage and work experience. Discuss if the criticism is consistent with our data.
  

fx B C D E F G H K L M N O P Q 1 employer wage hours 1Q KW educ exper tenure age 2 74 marriage gender urban sibs 15 562 40 27 brthord meduc feduc 11 14 3 15 1792 40 118 47 U 34 married Male Y 10 6 6 11 16 19 4 20 471 42 19 34 married Female Y 12 101 34 12 12 13 25 1053 38 31 married Female 8 114 35 7 10 16 12 6 30 635 40 32 married Male 128 11 35 11 18 8 7 13 34 666 36 single Male 75 129 16 40 16 18 8 8 12 43 1239 38 married Male 45 109 18 18 44 12 9 16 4 49 1155 40 38 married Male 102 36 10 12 10 16 12 5 55 462 34 married Male 40 112 12 11 35 12 11 11 1 67 442 60 82 29 married Female 32 12 12 12 12 72 2310 33 married Male A O H U W W N N N OH W N NO WH 12 40 114 O 55 12 18 9 13 12 7 87 857 35 38 married Male 80 39 KKK