for the 8th week using weights of 3, 2, and 1 (where the most recent weekreceives the highest weight). (Round all forecasts to the nearest whole unit.)b.Calculate the MAD for this forecast.c. What does the MAD indicate?iii.The number of students enrolled in Spring Valley Elementary school has been steadilyincreasing over the past five years. The School Board would like to forecast enrolmentfor years 6 and 7 in order to better plan capacity. The past five years enrolment isindicated in table 3:Table 3YearEnrollment1220224532564289310Assuming a linear trend, use the tabular method to derive values for:a. the slopeb. the interceptc. Forecast period 6 enrollment. i.Differentiate between independent and dependent variable in forecasting.The last seven weeks of sales at KC car dealership can be seen in Table 2 below.ii.Table 2WeekSales125230327431527297308Use a three-period weighted-moving average forecast to determine a forecastа.

Answered: for the 8th week using weights of 3, 2,…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.7: Exponential Smoothing Models

Problem 29P: The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building...

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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 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?
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?
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_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?
12. Under the bottom-up approach, a central person or persons take the responsibility for forecasting and preparing an overall forecast. Select one: True False
To have a stable forecasting tool when using the simple moving average method, what value of N (the number of periods) should a firm choose among the following choices? a. 3b. 2c. 8d. 6
Explain the difference between qualitative and quantitative approaches to forecasting. Describe three (3) qualitative methods used in forecasting. Given the following data of demand for shopping carts at a leading supermarket. Prepare a forecast for period 6 using each of the following approaches: Period 1 2 3 4 5 Demand 60 65 55 58 64 A three-period moving average. A weighted average using weights of .50 (most recent), .20 and .30. Exponential smoothing with a smoothing constant of .40. The manager of a large cement production factory in Road Town, Tortola has to choose between two alternative forecasting techniques. His production staff used both techniques in order to prepare forecasts for a six-month period (See table below). Using MAD as a criterion, which technique has the better performance record? FORECAST MONTH DEMAND TECHNIQUE 1 TECHNIQUE 2 1 492 488 495 2 470 484 482 3 485…
9) Gasoline sales Times Series week sales (1000s of gallons 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 With the above gasoline time series data, show the exponential smoothing forecast using alpha = 0.1 i)Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of Alpha= 0.1 or alpha=0.2 for the gasoline sales time series? ii)Are the results the same if you apply MAE as the measure of accuracy? iii)What are the results if MAPE is used?
Your manager is trying to determine what forecasting method to use. Based on the following historical data, calculate the following forecasts and specify what procedure you would utilize. Month Actual Demand 1 64 2 67 3 69 4 65 5 71 6 73 7 76 8 77 9 77 10 82 11 83 12 85 Calculate the simple three-month moving average forecast for periods 4–12.(Round your answers to 3 decimal places.) Month Actual Demand 4 66.667 5 67.000 6 68.333 7 69.666 8 73.333 9 75.333 10 76.666 11 78.666 12 80.666 Calculate the weighted three-month moving average for periods 4–12 using weights of 0.30 (for the period t−1); 0.20 (for the period t−2), and 0.50 (for the period t−3). (Do not round intermediate calculations. Round your answers to 1 decimal place.) Month Actual Demand 4 66.7 5 67.0 6 68.3 7 69.7 8 73.3 9 75.3…
Explain what are the use of a time series forecasting and discuss what assumption are made ?

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