The Dean of a faculty wants to forecast student enrolments for this academic year based on the following historical data: (5 years ago enrolment was 11770 ), (4 years ago enrolment was 15251), (3 years ago enrolment was 15785 ), (2 years ago enrolment was 16076 ) and in the last year enrolment was 19001 . What is the forecast for this year using exponential smoothing with alpha=0.58999997 , if the forecast for two years ago was :17623 a. 16710.27 b. 18061.801 c. 17801.75 d. 17386.035

The Dean of a faculty wants to forecast student enrolments for this academic year based on the following historical data: (5 years ago enrolment was 11770 ), (4 years ago enrolment was 15251), (3 years ago enrolment was 15785 ), (2 years ago enrolment was 16076 ) and in the last year enrolment was 19001 . What is the forecast for this year using exponential smoothing with alpha=0.58999997 , if the forecast for two years ago was :17623 a. 16710.27 b. 18061.801 c. 17801.75 d. 17386.035

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 40P: The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels....

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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?
At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.
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?
Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data: Week Number of students6 Weeks ago 515 Weeks ago 794 Weeks ago 833 Weeks ago 892 Weeks ago 71Last Week 93 What is this week's forecast using exponential smoothing with alpha = 0.3 , if the forecast for two weeks ago was 77 ? a. 75.2 b. 78.8 c. 69.86 d. 80.54
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant (a) of 0.30 and a starting forecast of 415.00, the following sales forecast has been developed: Forecasted Year Sales Sales 2005 455 415.00 2006 510 427.00 2007 516 451.90 2008 570 471.13 2009 585 500.79 The MAD for a forecast developed using exponential smoothing with a = 0.30 is 74.04 sales (round your response to two decimal places). Forecasted sales for years 2006 through 2010 using exponential smoothing with a = 0.60 and a starting forecast of 415.00 are (round your responses to two decimal places): Year 2005 2006 2007 2008 2009 2010 Forecasted Sales 415.00 439 481.6 502.24 542.9 568.12 The MAD for a forecast developed using exponential smoothing with a = 0.60 is decimal places). sales (round your response to two
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant (a) of 0.30 and a starting forecast of 415.00, the following sales forecast has been developed: Forecasted Year Sales Sales 2005 455 415.00 2006 510 427.00 2007 516 451.90 2008 570 471.13 2009 585 500.79 The MAD for a forecast developed using exponential smoothing with a = 0.30 is sales (round your response to two decimal places).
The monthly sales (in units) for a refrigerator in April 2021 through September 2021 were as follows: 42, 56, 49, 41, 56, 59 What is the forecasted sales in August 2021 if you use exponential smoothing with a smoothing constant 0.31? Assume the forecast in April 2021 was 44 units. Use at least 4 decimals.
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant (a) of 0.30 and a starting forecast of 415.00, the following sales forecast has been developed: Forecasted Year Sales Sales 2005 455 415.00 2006 510 427.00 2007 516 451.90 2008 570 471.13 2009 585 500.79 The MAD for a forecast developed using exponential smoothing with a = 0.30 is 74.04 sales (round your response to two decimal places). Forecasted sales for years 2006 through 2010 using exponential smoothing with a = 0.60 and a starting forecast of 415.00 are (round your responses to two decimal places): Year 2005 2006 2007 2008 2009 2010 Forecasted Sales 415.00 439 481.6 502.24 542.9 568.12 The MAD for a forecast developed using exponential smoothing with a = 0.60 is 51.05 sales (round your response to two decimal places). Forecasted sales for years 2006 through 2010 using exponential smoothing with a =…
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant (a) of 0.30 and a starting forecast of 415.00, the following sales forecast has been developed: Forecasted Year Sales Sales 2005 455 415.00 2006 510 427.00 2007 516 451.90 2008 570 471.13 2009 585 500.79 The MAD for a forecast developed using exponential smoothing with a = 0.30 is 74.04 sales (round your response to two decimal places). Forecasted sales for years 2006 through 2010 using exponential smoothing with a = 0.60 and a starting forecast of 415.00 are (round your responses to two decimal places): Year 2005 2006 2007 2008 2009 2010 Forecasted Sales 415.00
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant (a) of 0.30 and a starting forecast of 410.00, the following sales forecast has been developed: Forecasted Year Sales Sales 2005 450 410.00 2006 495 422.00 2007 518 443.90 2008 570 466.13 2009 585 497.29 The MAD for a forecast developed using exponential smoothing with a = 0.30 is 75.73 sales (round your response to two decimal places). Forecasted sales for years 2006 through 2010 using exponential smoothing with a = 0.60 and a starting forecast of 410.00 are (round your responses to two decimal places): Year 2005 2006 2007 2008 2009 2010 Forecasted Sales 410.00 434.00 470.60 499.04 541.62 567.65 The MAD for a forecast developed using exponential smoothing with a = 0.60 is sales (round your response to two decimal places).
The number of internal disk drives (in million) made at a plant in Taiwan during the past 5 years follows: Year Disk Drives 1 142 2 156 3 184 4 204 5 210 a) Using simple linear regression the forecast for the number of disk drives to be made next year= 234.4 disk drives b) The mean squared error (mse) when using simple linear regression=[___] drives^2 (round your response to one decimal place)
Complete the forecasting worksheets for: Naïve Average Moving Average Weighted Moving Average using the weights of .8, .15, and .05 with .8 being the most current, then .15, then .05 ExponA using and alpha level of .75 ExponB will automatically be .25 when A is .75 Exponential Solver What is the best alpha level as determined by the Exponential Solver? Which is the best forecasting option for MAE? What is the MAE? Which is the best forecasting option for MAPE? What is the MAPE? Period Sales 1 115 2 118 3 128 4 122 5 135 6 128 7 135 8 132 9 132 10 135