After graduation, you take a position at Top-Slice, a well-known manufacturer of golf balls. One of your duties is to forecast monthly demand for golf balls. Using the following data, you developed a regression model that expresses monthly sales as a function of average temperature for the month: Monthly sales = -202.2+86.5x (average temperature) Click the icon to view the additional data. a. Show how the a and 6 values of -202.2 and 86.5 were calculated. Calculate the slope coefficient, 6 (enter your responses as whole numbers). (745) 12 12 86.5 More Info March 2017 April May June July August September October November December January 2018 February Monthly Sales 5,300 3,990 5,700 6,520 7,600 7,420 6,710 4,870 3,990 3,900 3,320 2,670 Temperature 51 56 64 80 79 87 83 67 58 41 39 40 I X

The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT WINE 1 270 2 356 3 398 4 456 5 358 6 500 7 410 8 376 Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8. Note: Round your intermediate calculations and final answer to the nearest whole number.

Use the data set below to answer the following questions: [Gunakan set data di bawah untuk menjawab soalan-soalan berikut:] Table 1: Monthly sales unit IJadual 1: Unit jualan bulanau) Month Sales Units [Bulan] 1 [Unit Jualan] 1100 2 1200 3 1450 4 1800 2100 2700 i) Calculate the three-period simple moving average forecasts for months 4, 5 and 6. (Hitunskau rawalan pALata bergerak nudak weNEgUrakan empat-tenroh untuk bulau 5 dan 6.) Calculate the four-period weighted moving average forecasts for months 5 and 6 usıng weights of 0.05, 0.15, 0.30, and 0.50 from the earliest period to the latest period, respectively.

what are the differences between the following models? 1) Moving average models 2) Simple exponential smoothing 3) Holt's exponential smoothing 4) Winter's exponential smoothing 5) The Bass model In your answer, write down the equation for each model.  What does each variable mean?  Finally, why would I use one model as opposed to the others?  For example, the Bass Model is used to forecast the adoption rate for new innovations, or sigmoid shaped growth.

can you make an operations management analysis for this forecasting

The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October Actual Demand 105 82 110 112 108 106 130 120 Forecast Demand 100 108 97 98 108 102 105 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places).

The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October For the given forecast, the tracking signal = = MADS (round your response to two decimal places). November December Actual Demand 100 80 1/10 115 105 110 125 120 Forecast Demand 100 104 99 101 104 104 105 109

Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June July August Number of Oil Changes 38 55 56 60 58 01 70 52 a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For January, let X=1; for February, let X 2; and so on. The forecasting model is given by the equation Y=X (Enter your responses rounded to two decimal places)

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 17 12 15 12 18 13   Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.   (a) mean absolute error MAE =    (b) mean squared error MSE =    (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =  %   (d) What is the forecast for week 7?

Can you please solve all parts of the question manually. Thank you!