a. Using POM for Windows' least squares-linear regression module, develop a relationship to forecast production ratings from test scores. (Round your responses to three decisand include a minus sign if necessary.)Y= - 23 + .945 xwhere Y = Production rating and X = Test score.b. If a worker's test score was 54, what would be your forecast of the worker's production rating? 51. (Enter your response as an integer.)c. Comment on the strength of the relationship between the test scores and production ratings.The coefficient of correlation for the least-squares regression model isand the coefficient of determination is(Enter your responses rounded to three decimal places.)More infoTestScoreProductionRatingProductionTestWorkerWorkerRatingScoreA5543K5857B3843757593876748D86773126E88826249F66682425G5547Q7884Clear allCheck5046343241415158J6974T3930PrintDoneLLMN OPoRS

Coefficient of correlation = R Coefficient of Determination = R^2

Answered: c. Comment on the strength of the…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 42P: The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars)...

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Under what conditions might a firm use multiple forecasting methods?
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?
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?
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.
The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Pints Used 350 370 410 381 371 378 a) The forecasted demand for the week of October 12 using a 3-week moving average = 376.67 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.20, 0.35, and 0.45, using 0.45 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.)
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of Pints Used August 31 360 September 7 389 September 14 412 September 21 383 September 28 366 October 5 374 a) The forecasted demand for the week of October 12 using a 3-week moving average LOADING... = 374.33374.33 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.35, and 0.50, using 0.50 for the most recent week, the forecasted demand for the week of October 12 = 372.55372.55 pints (round your response to two decimal places and remember to use the weights in appropriate order — the largest weight applies to most recent period and smallest weight applies to oldest period.) c) If the forecasted demand for the week of August 31 is 360 and α = 0.20, using exponential smoothing,…
joxNjE1/a/NTE1MD92MZK5MDY1/details Open with Google Docs 1. National Mixer, inc. sells can openers. Monthly sales for a seven-month period were as follows: Sales Month (000units) Feb 19 Mar 18 Apr May June 15 20 18 July Aug 22 20 Forecast September sales using each of the following: A The Naive Approach B. Three month moving average C.A weighted moving average using 0.60 for the recent month, 0.30 for two months ago, and 0.10 for three months ago D. Exponential smoothing with a smoothing constantof 0.20 E Calculate the forecast errors for Moving Average, Weighted Moving Average and Exponential Smoothing, this includes: MAD, MSE and MAPE Page 2 1 3
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week 1 2 3 4 5 Obtain the error measures. (Enter your responses rounded to two decimal places.) CFE MSE Sales Find the coefficient of determination (²). The coefficient of determination r² = 0. (Enter your response rounded to two decimal places.) 44459 46 51 58 Use trend projection with regression to forecast sales for weeks 10-13. What are the error measures (CFE, MSE, 6, MAD, and MAPE) for this forecasting procedure? How about r²? Obtain the trend projection with regression forecast for weeks 10-13. (Enter your responses rounded to two decimal places.) Forecast, Ft Period 10 11 12 13 Week 6 69809 7 Sales 54 63 53 61 MAD U MAPE %
September 14 September 21 September 28 October 5 412 381 371 378 a) The forecasted demand for the week of October 12 using a 3-week moving average=pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.35, and 0.50, using 0.50 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.)
Plot the table and give at least three observations from the plot according to the given data Weeks Calls 3 month Weighted Moving Average Error =Abs (Actual -Forecasted) (Sum of Absolute percent error) 1 50 2 35 3 25 4 40 31.42857143 8.571428571 21.42857143 5 45 35 10 22.22222222 6 35 40.71428571 5.714285714 16.32653061 7 20 38.57142857 18.57142857 92.85714286 8 30 27.85714286 2.142857143 7.142857143 9 35 27.85714286 7.142857143 20.40816327 10 20 31.42857143 11.42857143 57.14285714 11 15 25.71428571 10.71428571 71.42857143 12 40 19.28571429 20.71428571 51.78571429 13 55 30 25 45.45454545 14 35 45 10 28.57142857 15 25 41.42857143 16.42857143 65.71428571 16 55 32.14285714 22.85714286 41.55844156 17 55 43.57142857 11.42857143 20.77922078 18 40 50.71428571…
K The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 - Pints Used 350 370 412 378 371 378 a) The forecasted demand for the week of October 12 using a 3-week moving average = 375.67 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.30, and 0.55, using 0.55 for the most recent week, the forecasted demand for the week of October 12 = decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) pints (round your response to two

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