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- 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_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.
- 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 table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- 1. A simple three-month moving average. 2. A three-period weighted moving average using weights of 1, 2, and 3. Assign the highest weight to the most recent data. 3. Exponential Smoothing when α= .6 and the forecast for March is 350. 4. Determine which of the three forecasting techniques is the most accurate using MAD.Year Season Sales 2018 Winter 40 2018 Spring 29 2018 Summer 31 2018 Fall 40 2019 Winter 102 2019 Spring 87 2019 Summer 96 2019 Fall 132 2020 Winter 105 2020 Spring 93 2020 Summer 105 2020 Fall 117 2021 Winter 141 2021 Spring 39 2021 Summer 114 2021 Fall 123 What is the slope of the trend equation obtained by linear regression? Round to two decimal digits. What is the intercept of the trend equation obtained by linear regression? Round to two decimal digits. What is the seasonal index for Spring? Round to two decimal digits. The quarter number for Winter of 2018 is 1. What is the quarter number for Spring of 2025? What is the trend based forecast for Spring of 2025. Round to a whole number. What is the seasonally adjusted trend based forecast for Spring of 2025? Please do not use excel to find the slope and intercept, thank you so much!
- The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER 1 2 5678AWN 3 4 8 SALES 219 237 208 171 169 Quarter 9 10 11 12 192 157 132 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast1. The table below shows the sales figure for a brand of shoe over the last 12 months. MONTHS SALES January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- 1. A simple three month moving average.ii. A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data.iii. Exponential Smoothing when a= .6 and the forecast for March is 350.
- The table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- A simple three month moving average. A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. Exponential Smoothing when α= .6 and the forecast for March is 350. Determine which of the three forecasting technique is the most accurate using MAD.Please answer parts i, ii and iii of the below question. The table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- i) A simple three month moving average. ii) A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii) Exponential Smoothing when α= .6 and the forecast for March is 350.My App is a small but growing start-up that sees demand for several of its apps increasing quickly. The table below shows the last six months of downloads. Use a forecast for the first month of 220,000, an initial trend forecast of 35,000, and smoothing parameters of 015 for both demand smoothing and trend smoothing Month (t) Monthly Application Downloads Forecast for Next Month Trend 220,000.00 35,000.00 200,000 2 250, 100 334,000 380,000 440,000 500,000 (Round your answers to 2 decimal places.) Complete the table above, filling in the "Forecast for next month" and "Trend" columns, using double a. exponential smoothing (Round your answers to 2 decimal places.) Month 7's forecast is b.