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. 6 Period 13 14 15 16 6 740 7 782 12 663 1 2 3 4 5 8 9 10 11 Period Transactions 714 716 838 634 694 712 719 837 825 Obtain the trend projection with regression forecast (Enter your responses rounded to the nearest whole number) Forecast, F
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- 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 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_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?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. Week 1 2 3 4 5 6 7 8 9 10 11 12 Transactions 512 527 631 434 482 539 577 518 526 636 623 461
- Company XYZ is a movie distribution company. It has kept records of total annual movie ticket sales for one community over last 4 years: Actual Sale 2015 96,480 94,300 97,800 92,100 2016 2017 2018 You used the moving average method to forecast 2018 sale using 2015, 2016 and 2017 information. And then you used the exponential smoothing model to forecast 2019 sale based on 2018 information, using alpha = 0.3. What is the forecasted 2019 sale? 8:42 pmFollowing 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?Room registrations in the Toronto Towers Plaza Hotel have been recorded for the past 9 years. To project future occupancy, management would like to determine the mathematical trend of guest registration. This estimate will help the hotel determine whether the future expansion will be needed. Given the following time-series data, develop a regression equation relating registrations to time (e.g., a trend equation). Then forecast year 11 registrations. Room registrations are in the thousands: Sr. No Year Registration (000) 1 2011 17 2 2012 16 3 2013 16 4 2014 21 5 2015 20 6 2016 20 7 2017 23 8 2018 25 9 2019 24
- The number of fishing rods selling each day is given below. Perform analyses of the time series to determine which model should be used for forecasting. 3 day moving average analysis 4 day moving average analysis 3 day weighted moving average analysis with weights W1=0.2, W2=0.3 and W3=0.5 with W1 on the oldest data. Exponential smoothing analysis with A=0.3 Which model provides a better fit of the data? Forecast day 13 sales of fishing rods using the model chosen in part (e) Day Rods Sold 1 60 2 70 3 110 4 80 5 70 6 85 7 115 8 105 9 65 10 75 11 95 12 85 Please read the relevant article, found in the VLE, before answering the question. Discuss the process and findings of the study of the article. Suggest a possible study that could be done at your current or past job that could use a similar methodology and analysis.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.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)