Q4ABC University wants to develop forecasts for next year's quarterly enrollment. It has collectedquarterly enrollments for the past two years. It has also forecast total annual enrollment for nextyear to be 95,000 students. What is the forecast for each quarter of next year?Enrollment (in 000')QuarterYear 1Year 2Fall2425Winter2322Spring1819Summer1517

Answered: Q4 ABC University wants to develop…

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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Similar questions

Under what conditions might a firm use multiple forecasting methods?
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?
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 file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?
The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend, orassociative) that would be most appropriate for predicting:c. Demand for vacations on the moon.
The past two years sales at ACSR Inc. were 3 million and 5 million. Their forecast team used a two-period moving average to forecast its sales this year. But the actual sales for this year were 5 million. Now, the forecast team wants to forecast its sales for next year by using exponential smoothing with alpha equals 0.6. What is the forecast using exponential smoothing with alpha = .6? 2. If we decide to use an alpha of .2 instead of .6, will we be ‘weighting the error from the previous period higher or the Forecast from the previous period higher? Explain briefly or show using math! (In this question I am asking if we change the alpha to a lower alpha, what will be the effect – what will we be ‘weighing’ as more important?)
The sales of Bluetooth Headphones at the Dubai Electronics Enterprises in Jebel Ali, UAE, over the past 4 months have been 100, 110, 120, and 130 units (with 130 being the most recent sales). Develop a moving-average forecast for next month, using the following techniques: 5B. If next month's sales turn out to be 140 units, forecast the following month's sales (months) using a 4-month moving average.
Specific motors produces electronic motors for power-actuated valves for the Medicalconstruction industry. Specific's production plant has operated at near capacity forover a year now. JOSEPH Bakkabulindi, the plant manager thinks that the growth insales will continue, and he wants to develop a long- range forecast to be used to planfacility requirements for the next 3 years. Sales records for the past 10 years havebeen accumulated: N.B: Show all the workings. Solve with Linear regression. Year Annual sales (000's of units) Year Annual sales (000's of units 1 500 6 1,000 2 650 7 1,100 3 900 8 1,300 4 1,000 9 1,450 5 1,000 10 1,600
Sales of the Crown Gems have been increasing over the past five years. The operations manager has estimated sales in 2017 to be 410 Crown Gems. Using exponential smoothing with a weight of α = 0.30, the forecasts for 2017 through 2022 were developed. The forecasts for 2017 through 2022 is: Year Forecast 2016 450 2017 450 2018 463.5 2019 479.85 2021 504.795 2022 528.5565 a. Advise Crown Gems of the benefits associated with this method of forecasting. b.Caution the manager on the limitations associated with your forecast.

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