Do the analysis for the above sample information using the appropriate statistic

Question

Do the analysis for the above sample information using the appropriate statistical method to determine whether Jensen Tire & Auto should purchase the maintenance contract:

* I'M HAVING TROUBLE FIGURING OUT THE 95% CONFIDENCE INTERVAL AND PREDICTION INTERVALS SECTION OF THE REPORT. I HAVE TO USE DATA ANALYSIS PLUS BUT I CAN'T FIGURE OUT HOW TO DO THE "PREDICTION INTERVAL" TESTING BECUASE I'M CONFUSED AS TO WHAT MY "GIVEN X RANGE" INPUT SHOULD BE WITH RESPECT TO THE ORIGINAL CASE STUDY... ANY HELP IS GREATLY APPRECIATED.

Weekly Usage (Hours) Annual Maintenance Expense 13 17.0 10 22.0 20 30.0 28 37.0 32 47.0 17 30.5 24 32.5 31 39.0 40 51.5 38 40.0 25 19.5 24 49.0 20 31.7 22 41.3 12 40.5 11 37.4 25 14.4 19 35.0 25 34.1 21 35.2 22 26.8 29 24.4 17 29.7 12 35.2 10 20.1 28 37.3 10 33.2 16 31.1 30 41.6 13 29.9 Case Study: Maintenance Contract Business decision making is something that management must to do on a daily basis. Jensen Tire & Auto is a family owned auto service company. In recent months, business has been slow so in an effort to reduce cost, the company is deciding on whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine, which costs $5,000 per year, instead of maintaining their own machine. The owner feels that maintenance expense should be related to usage so he collected a random sample of 30 weeks of weekly usage (hours and annual maintenance expense (in hundreds of dollars). For each week, the following variables were recorded Weekly usage (hours) Annual Maintenance Expense (S100s) However, he is unsure how to do the analysis. Knowing you are about to finish the course in business analytics, your manager recommended you to the owner and you are now appointed to do the analysis for the above sample information using the appropriate statistical method to determine whether Jensen Tire & Auto should purchase the maintenance contract. Your report should have the following qualities: Your report must be in a genuine report format with problem definition, analysis and final conclusion. All important analysis steps need to be followed to arrive at the model to be used for prediction. Attach the details of your analysis at the end of your report. Very simplistic analysis with insufficient details will be assigned a near zero credit. Just running Excel does not guarantee any credit Your final conclusion should use both the 95% confidence and prediction intervals. Improper use of these and corresponding wrong/sloppy interpretation is highly penalized. Use Data Analysis for Regression and then either Data Analysis Plus or the Regression Template provided on the course website for the intervals.

Explanation / Answer

SOl:

Run regression analysis

here independent variable=weekly usage

dependent variable=annual maintenance expense

run regression in excel

annual maintenance expense=22.467+0.497(weekly usage)

is model to be used.

slope=0.497

y intercept=22.467

95% CI for weekly usage=0.121,0.872

lower limit=0.121

upper limit=0.872

Model is significant as p<0.05

R sq=0.207=20.7% variance is annual maintenance expense is explained by model.

Rest(100-20.7) is unexplained by model.

correlation coefficient=r=0.455

there exists a moderative positive relationship between annual maintenance expense and weekly usage.

Coefficients Standard Error Intercept 22.46731 4.216687 Weekly Usage (Hours) 0.496709 0.183647

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