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 hasincreased the number of customers now using its automatic teller machines to that point that more machines are required. The following table provides the number of automatic tellertransactions by week. Use trend projection with regression to forecast usage for weeks 13 - 16.Period1235689101112Transactions715717832634688741780713727837824663Obtain the trend projection with regression forecast. (Enter your responses rounded to the nearest whole number.)PeriodForecast, F,13141516

Forecasting is the process of estimating the future demand based on previous information or historic…

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 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 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_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_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?
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 its automatic teller machines to that point that more machines are required. The following table provides the number of automatic teller transactions by week. Use trend projection with regression to forecast usage for weeks 13-16. 11 2 12 10 8 3 4 9 5 Period Transactions 716 838 634 694 712 719 837 825 663 Obtain the trend projection with regression forecast (Enter your responses rounded to the nearest whole number) Forecast, F 1 714 Period D 13 14 15 16 6 740 7 782
Following table shows the weekly sales of smart phones at electronic retail store: Week Number of smart phones Sold Forecast using 3 period moving average Error Forecast using exponential smoothing (with α =0.4) Error 1 48 2 41 3 55 4 64 5 62 6 55 7 8 Answer the following questions based on the data given above. Show all your calculations. What is the expected sales for the 7th week based on 3 period moving average. What is the forecast for the 8th week using the same method if the actual sales for week 7 happens to be 70? What is the expected sales for the 7th week based on exponential smoothing with α = 0.3? Which of the above two forecasting method is better based on MSE? Explain why?
Forecasting The manager of a popular tourist resort wants to use the manual trend projection forecasting technique and exponential smoothing without trend to forecast room occupancy at the resort for the next 4 years. Using a numerical example, demonstrate how these techniques can be used to do the forecast.
Professor Very Busy needs to allocate time next week to include time for office hours. He needs to forecast the number of students who will seek appointments. He has gathere the following data: Week 6 weeks ago 5 weeks ago 4 weeks ago 3 weeks ago 2 weeks ago # Students 83 110 95 80 65 50 Last week What is this week's forecast using trend adjusted (double) smoothing with alpha=0.5 and beta = 0.1, if the smoothed forecast for last week was 60, and the smoothed trend estimate for last week's forecast was -5? 49.3 O 50.6 47.3 65.4 42.7
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Jan Number of Accidents 25 Feb 48 Mar 64 Apr 100 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): y = -1 + 24.10 x Using least-squares regression, the forecast for the number of accidents that will occur in the month of May response as a whole number). = accidents (enter your
Forecasting with Linear Regression The company VID-CO-19 has manufactured swim suits for men, women, and children for 10 years. The company is located in Boston, Massachusetts. Swim suits have always had a higher demand during the months of April, May, June, July, August, and September. The demand has always been lower during the months of October, November, December, January, February, and March. TETT The real demand, based on sales of year 20X1 is the following (it starts with December of the previous year): Period Bimester Demand Season Average December-January February-March 1 100 90 2 200 180 3 April-May June-July August-September 900 910 4 3,000 2,100 4,000 4,900 October-November 300 350 VID-CO-19 has hired you as an Operations Management expert to help them to forecast demand for year 20X2 using the Linear Regression Method. What is the TOTAL "seasonalized" or "deseasonalized' forecasted demand for Quito-Ecuador in year 20X2? (write your answer rounded to two decimals)

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