6. Tutoring Center needs to allocate tutors this week for office appointments, so it needsto forecast the number of students who will seek appointments. The director hasgathered the following time series data recently:Time PeriodCodeStudent AppointmentsJan 6 - 10195Jan 13 - 17280Jan 20 - 24365Jan 27 - 31450a) What is the naïve forecast for the number of student appointments for TimePeriod 5 (Feb 3 – 7)?b) What is the 2 week moving average for Time Period 5?c) What is the 3 week moving average for Time Period 5?d) What is the forecast for Time Period 5 using exponential smoothing with alpha =0.2 and a forecast 90 for Time Period 3?e) Is demand for appointments increasing or decreasing?

Note: - Since we can answer only up to three subparts we will answer the first three(a, b, and c)…

Answered: 6. Tutoring Center needs to allocate…

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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Similar questions

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 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_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 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?
Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data: Week Number of students6 Weeks ago 515 Weeks ago 794 Weeks ago 833 Weeks ago 892 Weeks ago 71Last Week 93 What is this week's forecast using exponential smoothing with alpha = 0.3 , if the forecast for two weeks ago was 77 ? a. 75.2 b. 78.8 c. 69.86 d. 80.54
Given is a historical time series for job services demand in the prior 6 months. Month Demand 1 702 2 711 3 714 4 701 5 689 6 711 The Period 6 forecast by using weighted moving average with weights of 0.05, 0.25, 0.40, and 0.30 = (in 2 decimal places)
4 Trinity General Hospital had the following number of patient admissions during the past 8 weeksWeek Patient Admissions1 1202 1453 954 1125 1306 1107 1008 140 a. Develop a 3-week weighted average forecast forWeek 4 through 9 with weightsW1 = 0.2W2 = 0.3W3 = 0.5 b. Forecast patient admissions for week 9 using simpleexponential smoothing with α = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.
A distributor uses the following equation for forecasting demand of ski goggles: Y = 834 + 18*t, where t=0 in Spring of 2013. Each season is a period, so Summer 2013 would be t=1. His seasonal relatives are (Fall=1.2; Winter=1.4; Spring = 0.9; Summer= 0.8). What is his seasonalized forecast for Spring 2014? Plz do fast asap
An analyst must decide between two different forecasting techniques for weekly sales of rollerblades: a linear trend equation and the naive approach. The linear trend equation is Ft= 124 + 2t,and it was developed using data from periods 1 through 10. Based on data for periods 11 through20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSEare used?t Units Sold11 14712 14813 15114 14515 15516 15217 15518 15719 16020 165
Management of Davis’s Department Store has used time-series extrapolation to forecast retail sales for the next four quarters. The sales estimates are $100,000, $120,000, $140,000, and $160,000 for the respective quarters before adjusting for seasonality. Seasonal indices for the four quarters have been found to be 1.30, 0.90, 0.70, and 1.10, respectively. Compute a seasonalized or adjusted sales forecast? Develop an adjusted exponential forecast for a firm with the demand for bread as shown in the table below. week 1 2 3 4 5 6 7 8 Demands 700 685 648 717 713 728 754 762 Let α = 0.1 and β = 0.2. Previous average of Ft–1= 650, and let the initial trend adjustment, Tt–1 = 0? note please answer all the questions
A manager of a store that sells and installs spas wants to prepare a forecast for January, February, and March of next year. Her forecasts are a combination of trend and seasonality. She uses the following equation to estimate the trend component of monthly demand: Ft = 70 + 5t, where t = 0 in June of last year. Seasonal relatives are 1.10 for January, 1.02 for February, and .95 for March. What demands should she predict?

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