DumfriesNewcastleupIsle of ManUnited KingdoreScarboroughCardin09TrentIn the anyLogistix Tutorial assigned, students performed a Greenfield Analysis (GFA).What does GFA mean? What were the main inputs into the model that you eitherentered by hand or imported via the provided spreadsheet (hint: there were two ofthem)? The picture above shows a sample of a GFA experiment output. Explain whatthe output is showing here. What does this mean for a supply chain networkdesigner?The next higher-level analysis, network optimization considers constraints thatwould add complexity to the GFA and possibly create a different configuration. Whatare some of the constraints that go beyond what was considered in GFA?

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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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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?
Under what conditions might a firm use multiple forecasting methods?
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_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?
My App is a small but growing start-up that sees demand for several of its apps increasing quickly. The table below shows the last six months of downloads. Use a forecast for the first month of 220,000, an initial trend forecast of 35,000, and smoothing parameters of 015 for both demand smoothing and trend smoothing Month (t) Monthly Application Downloads Forecast for Next Month Trend 220,000.00 35,000.00 200,000 2 250, 100 334,000 380,000 440,000 500,000 (Round your answers to 2 decimal places.) Complete the table above, filling in the "Forecast for next month" and "Trend" columns, using double a. exponential smoothing (Round your answers to 2 decimal places.) Month 7's forecast is b.
"Your Capstone Courier Market Segment Analysis Report for the High End market shows a total demand of 10,0000 units for the coming year. You have a high end product and a count of your competitors products finds they have the equivalent of 3 High End products and one new High End product coming out on January 1. What is the best range for your unit sales forecast? O "1,500 to 2,000 units" O "2,400 to 2,600 units" O "1,900 to 2,100 units" O 2,200-2,300
I just need the last one please (:
Dic 2 - Time Series Analysis and F eBook Problem 6-01 (Algorithmic) Consider the following time series data. Thm Week 1 2 3 4 5 6 Value 20 13 15 11 19 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. a. Mean absolute error. If required, round your answer to one decimal place. b. Mean squared error. If required, round your answer to one decimal place. c. Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places. % d. What is the forecast for week 7? If required, round your answer to two decimal place.
OQ16
1
My App is a small but growing start-up that sees demand for several of its apps increasing quickly. The table below shows the last six months of downloads. Use a forecast for the first month of 215,000, an initial trend forecast of 50,000, and smoothing parameters of 0.05 for both demand smoothing and trend smoothing. Month (t) Monthly Application Downloads Forecast for Next Month 39:41 Trend 215,000.00 50,000.00 1 200,000 250,020 3 320,000 4 410,000 445,000 6. 496,000 (Round your answers to 2 decimal places.) Complete the table above, filling in the "Forecast for next month" and "Trend" columns, using double exponential smoothing. a. (Round your answers to 2 decimal places.) b. Month 7's forecast is:

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