Question: The file COSTEST 3 on the CD contains data on production runs at a manufacturing plant. There are two columns of data: y= COST is

The file COSTEST 3 on the CD contains data on production runs at a manufacturing plant. There are two columns of data:

y= COST is the total cost of the production run

x= NUMBER is the number of items produced during that run

Run the regression using COST as the dependent variable and NUMBER as the independent variable and use the result to help answer the following questions:

A: what is the estimated regression equation relating y to x?

B: What percentage of the variation in y has been explained by the regression?

C: Are Y and x linearly related? Conduct a hypothesis test to answer this question and use a 5% level of significance. State the hypotheses to be tested, the decision rule, the test statistic, and your decision. What conclusion can be drawn from the result of the test?

D. Estimate the fixed cost involved in the production process. Find a point estimate and a 95% confidence interval estimate.

E. Estimate the variable cost involved in the production process. Find point estimate and a 95 % confidence interval estimate.


Place this in a single workbook on separate sheet (Excel). Answer the question below the output and clearly label the answers. I don't want mere numbers for answers. Justify your answers by referring to the output and explain them in the context of the problem. You don't have to calculate any number which is found on the output, just use it. Write a quantitative report.

NUMBER COST

30 ...........94

35...........109

32..........99.5

33...........100

30..........91.5

29..........85.5

24..........80.5

20..........74.5

22.............79

27.............85

26..........81.5

29.............88

31.............96

34...........103

33...........103

32...........97

30.............90

28..........86.5

22..........77.5

23............81

25..........83.5

27..........82.5

25...........81

28...........85

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NUMBER COST SUMMARY OUTPUT 30 94 35 109 Regression Statistics 32 995 Multiple R 095440153 33 100 R S... View full answer

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