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 a) The forecasted demand for the week of October 12 using a 3-week moving average = 375 pints (round your response to two decimal places) b) Using a 3-week weighted moving average, with weights of 0.15, 0.25, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = 150.10 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.) Pints Used 360 389 410 381 366 378

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 a) The forecasted demand for the week of October 12 using a 3-week moving average = 375 pints (round your response to two decimal places) b) Using a 3-week weighted moving average, with weights of 0.15, 0.25, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = 150.10 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.) Pints Used 360 389 410 381 366 378

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

See similar textbooks

Similar questions

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_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.
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_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?
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 360 389 412 378 366 371 a) The forecasted demand for the week of October 12 using a 3-week moving average: to two decimal places). = pints (round your response
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 345 389 412 383 366 371 a) The forecasted demand for the week of October 12 using a 3-week moving average decimal places). pints (round your response to two
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: a) The forecasted demand for the week of October 12 using a 3-week moving average = Week Of August 31 September 7 September 14 September 21 September 28 October 5 pints (round your response to two decimal places). Pints Used 345 389 408 381 371 374
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 350 370 410 383 368 374 a) The forecasted demand for the week of October 12 using a 3-week moving average=pints (round your response to two decimal places).
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 September 7 September 14 September 21 September 28 345 370 410 378 368 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places).