Community Federal Bank in Dothan, Alabama, recently increased its fees to customers who use employees as tellers.Management is interested in whether its new fee policy has increased the number of customers now using itsautomatic teller machines to that point that more machines are required. The following table provides the number ofautomatic teller transactions by week. Use trend projection with regression to forecast usage for weeks 13-16.112121083495PeriodTransactions716838634 694712719 837 825 663Obtain the trend projection with regression forecast (Enter your responses rounded to the nearest whole number)Forecast, F1714PeriodD13 14 15 1667407782

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Answered: Community Federal Bank in Dothan,…

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_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_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?
Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table: Maroon 5 Tv Appearances 3 4 7 6 8 5 Demand for Guitars 3 6 7 5 10 7 b) Using the least-squares regression method, the equation for forecasting is (round your response to four decimal places): Y= _____+_____X C) The estimate for guitar sales if Maroon 5 performed on Tv 9 times =___ (round your response to 2 decimal places
Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend, orassociative) that would be most appropriate for predicting:a. Demand for Mother’s Day greeting cards.
Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table: Maroon 5 TV Appearances 3 4 8 6 7 7 Demand for Guitars 4 6 7 5 10 6 This exercise contains only parts b, c, and d. Part 2 b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): Y = enter your response here + enter your response herex
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.
Sales of Bluetooth Headphones at the Abdulla Electronics Enterprises in Model Town, India, 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 following techniques: a) 3-month moving average. b) 4-month moving average. c) Weighted 4-month moving average with the most recent month weighted 4, the preceding month 3, then 2, and the oldest month weighted 1. d) If next month’s sales turn out to be 140 units, forecast the following month’s sales (months) using a 4-month moving average.
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?)

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