The materials handling manager of a manufacturing company is trying to forecast the cost of maintenance for the company's fleet of over-the-road tractors. The manager believes that thecost of maintaining the tractors increases with their age. The following data was collected:YearlyMaintenanceYearlyMaintenanceAge(years)Age(years)Cost ($)Cost (S)6.58198.01,3945.51,2492.53636.51,2332.53827.06959.09646.09238.01,5736.08813.01,1787.01,0903.06667.01,7223.07497.51,187a. Use POM for Windows' least squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. (Enter your responsesrounded to three decimal places and include a minus sign if necessary.)Y = 365.727 + 110,721 Xwhere Y = Yearly maintenance cost in dollars and X= Age in years.b. If a section has 20 four-year-old tractors, what is the forecast for the annual maintenance cost? $|- (Enter your response rounded to two decimal places.)

The algebraic formulation of the regression lines is the Regression Equation. It's used to forecast…

a. Use POM for Windows' least squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. (Enter your responses rounded to three decimal places and include a minus sign if necessary.) Y = 365.727 + 110.721 X where Y Yearly maintenance cost in dollars and X= Age in years. b. If a section has 20 four-year-old tractors, what is the forecast for the annual maintenance cost? $ (Enter your response rounded to two decimal places.)

a. Use POM for Windows' least squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. (Enter your responses rounded to three decimal places and include a minus sign if necessary.) Y = 365.727 + 110.721 X where Y Yearly maintenance cost in dollars and X= Age in years. b. If a section has 20 four-year-old tractors, what is the forecast for the annual maintenance cost? $ (Enter your response rounded to two decimal places.)

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.4: Multiple Regression Models

Problem 17P: The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He...

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The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?
The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.
Under what conditions might a firm use multiple forecasting methods?
While analyzing their annual sales data (liters of wine sold per year) for the past 30 years, a vineyard found that after taking four successive differences, the resulting data had a mean of 2458 liters and looked like a stationary process (e.g. white noise). If the actual data for the past four years were 2018 - 2134 liters, 2017 - 2403 liters, 2016 - 2076 liters, and 2015 - 2290 liters. What would be a reasonable forecast for sales in 2019? Explain.
Room registrations in the Toronto Towers Plaza Hotel have been recorded for the past 9 years. To project future occu-pancy, management would like to determine the mathemati-cal trend of guest registration. This estimate will help the hotel determine whether future expansion will be needed. Given the following time-series data, develop a regression equation relat-ing registrations to time (e.g., a trend equation). Then forecast year 11 registrations. Room registrations are in the thousands:Year 1: 17 Year 2: 16 Year 3: 16 Year 4: 21 Year 5: 20Year 6: 20 Year 7: 23 Year 8: 25 Year 9: 24
Room registrations in the Toronto Towers Plaza Hotel have been recorded for the past 9 years. To project future occupancy, management would like to determine the mathematical trend of guest registration. This estimate will help the hotel determine whether the future expansion will be needed. Given the following time-series data, develop a regression equation relating registrations to time (e.g., a trend equation). Then forecast year 11 registrations. Room registrations are in the thousands: Sr. No Year Registration (000) 1 2011 17 2 2012 16 3 2013 16 4 2014 21 5 2015 20 6 2016 20 7 2017 23 8 2018 25 9 2019 24
An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data: (4 year ago Quantity sold was 10842), (3 year ago Quantity sold was 11881 ), (2 year ago Quantity sold was 16064 ) and the last year Quantity sold was 19273 . The previous trend line had predicted 12250 for three years ago, 13000 for two years ago and 13750 for last year. What was the mean absolute percent error (MAPE) for these forecasts? a. 16.95 b. 2739 c. 0.17 d. 2985
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Community Federal Bank in Dothan, Alabama, recently increased its fees to customers who use employees as tellers. Management is interested in whether its new fee policy has increased the number of customers now using its automatic teller machines to that point that more machines are required. The following table provides the number of automatic teller transactions by week. Use trend projection with regression to forecast usage for weeks 13–16. Week 1 2 3 4 5 6 7 8 9 10 11 12 Transactions 512 527 631 434 482 539 577 518 526 636 623 461
Sales of hair dryers at the Walgreens stores in Youngstown,Ohio, over the past 4 months have been 100, 110, 120, and 130units (with 130 being the most recent sales).Develop a moving-average forecast for next month, usingthese three techniques:a) 3-month moving average.b) 4-month moving average.c) Weighted 4-month moving average with the most recentmonth weighted 4, the preceding month 3, then 2, and theoldest month weighted 1.d) If next month’s sales turn out to be 140 units, forecast the following month’s sales (months) using a 4-month mov-ing average.
Chart and Regression analysis : What does the intercept predict? X: C16 (number of cars on the sales lot) versus Y: C17 (cars sold per day) Equation: y=2.9x + 14.5 Slope:2.9 Intercept:14.5 Does the intercept mean the intercept is 14.5 means that the cars sold per day( Y) predicted number of cars on sale lot(X) to be 14.5, but this intercept has no meaning. So, I will not use to predict cars sold per day?