Actual sales of a company (in millions of dollars) for January through April are shown below. Month Sales January 17 February 26 March 31 April 39 May (a) Use a - 0.3 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error values and MSE to two decimal places.) Month Sales Squared Forecast Error Forecast January 17 February 26 March 31 April 39 May MSE (b) Use a = 0.1 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error values and MSE to two decimal places.) Month Sales Forecast Squared Forecast Error January 17 February 26 March 31 April 39 Мay MSE =
Actual sales of a company (in millions of dollars) for January through April are shown below. Month Sales January 17 February 26 March 31 April 39 May (a) Use a - 0.3 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error values and MSE to two decimal places.) Month Sales Squared Forecast Error Forecast January 17 February 26 March 31 April 39 May MSE (b) Use a = 0.1 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error values and MSE to two decimal places.) Month Sales Forecast Squared Forecast Error January 17 February 26 March 31 April 39 Мay MSE =
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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Transcribed Image Text:Actual sales of a company (in millions of dollars) for January through April are shown below.
Month
Sales
January
17
February
26
March
31
April
39
May
(a) Use a = 0.3 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error
values and MSE to two decimal places.)
Month
Sales
Forecast
Squared Forecast Error
January
17
February
26
March
31
April
39
May
MSE =
(b) Use a = 0.1 to compute the exponential smoothing values for sales. Compute MSE and forecast sales for May. Assume the forecast for the initial period (January) is 17. Show all of your computations from February through May. (Round your squared forecast error
values and MSE to two decimal places.)
Month
Sales
Forecast
Squared Forecast Error
January
17
February
26
March
31
April
39
Мay
MSE =
Transcribed Image Text:(c) Based on MSE, which a provides a better forecast? Explain why?
O The exponential smoothing using a = 0.1 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.3.
O The exponential smoothing using a = 0.1 provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.3.
O The exponential smoothing using a = 0.3 provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.1.
O The exponential smoothing using a = 0.3 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.1.
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