Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 4 5 6 Value 19 14 17 12 18 15 a)  Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 19   2 14   3 17   4 12   5 18   6 15     What is Compute MSE?  (Round your answer to two decimal places.) MSE = ? What is the forecast for week 7?

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_28.xlsx contains monthly retail sales of U.S. liquor stores. 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?

Please help with correct answers in details: Step by step Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in Bennington, Vermont, over the past 12 weeks. Week Sales (1,000sof gallons) 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 (a) Compute four-week and five-week moving averages for the time series. Week Time SeriesValue 4-WeekMovingAverageForecast 5-WeekMovingAverageForecast 1 17     2 21     3 20     4 24     5 18     6 17     7 21     8 19     9 22     10 21     11 16     12 22     b) Compute the MSE for the four-week moving average forecasts. (Round your answer to two decimal places.) c) Compute the MSE for the five-week moving average forecasts. (Round your answer to two decimal places.) d) What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation? MSE for the three-week moving average is 9.65.…

The following time series shows the sales of a particular product over the past 12 months. Month Sales 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110   (a)Use ? = 0.4 to compute the exponential smoothing values for the time series. (Round your answers to two decimal places.) Month t Time Series Value Yt Forecast  Ft 1 105   2 135   3 120   4 105   5 90   6 120   7 145   8 140   9 100   10 80   11 100   12 110     (b)Use a smoothing constant of ? = 0.6 to compute the exponential smoothing forecasts. (Round your answers to two decimal places.)     Month t Time Series Value Yt Forecast  Ft 1 105   2 135   3 120   4 105   5 90   6 120   7 145   8 140   9 100   10 80   11 100   12 110

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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

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 QUARTER SALES 1. 211 5 155 235 6 198 3 206 7 154 4 190 8 142 Use regression and seasonal indexes to forecast quarterly sales for the next year. (Do n ot round intermediate calculations. Round your answers to the nearest whole number.) Answer is complete but not entirely correct. Quarter Forecast 142 8 157 8 121 8 10 11 12 103

The total sales of a company doing business from Monday through Saturday.   Number of Motor vehicles ('000)           Mon Tue Wed Thurs Fri. Sat.   Week 1 34 30 21 28 32 43 Week 2 35 28 23 27 31 40 Week 3 36 27 25 25 33 41 Week 4 32 29 23 23 38 38 (c) Illustrate the time series graph by including the data (y) and trend (t).