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Prev Consider the following time series representing the average number of points scored by teams in NBA games over a 14-day period. Step 1 of

Prev Consider the following time series representing the average number of points scored by teams in NBA games over a 14-day period.
Step 1 of 5: Using a smoothing constant (alpha) = 0.1 and assuming F1 = Y1, calculate the exponential smoothing forecasted value for t = 15. Round to 2 decimal places.
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Consider the following time series representing the average number of points scored by teams in NBA games over a 14 -day period. Use this info to answer the questions below. - Special Text to paste properly into Excel. Step 1 of 5 : Using a smoothing constant (alpha) =0.1 and assuming F1=1. calculate the exponential smoothing forecasted value for t=15 Round to 2 decimal places: Step 4 of 5: Calculate the MAPE (Mean Absolute Percent Error) for the Simple Exponential Smoothing forecasts for alpha = 0.7 that you calculated for time periods t=1 thru 14 in step 3 . Do NOT include the forecast for t=15, Express as a percent and round your answer to one decimal place (that is, 0.125 or 12.5% should be entered as 12.5). Step 2 of 5: Calculate the MAPE (Mean Absolute Percent Error) for the Simple Exponential Smoothing forecasts for alpha =0.1 that you generated for time periods t=1 thru 14 in step 1 . Do NOT include the forecast for t=15. Express as a percent and round your answer to one decimal place (that is, 0.125 or 12.5% should be entered as 12.5). Step 5 of 5: Considering the two MAPE values from the alpha =0.1 forecasts and the alpha =0.7 forecasts, which smoothing constant is preferted and why? Answer 0.5 Points Alpha =0,1 is preferred, because the MAPE is smaller indicating more error, which is a good thing. Alpha = 0.1 is preferred, becouse the MApe is smaller indicating less error, which is a good thing. Alpha =0.7 is preferred, because the MAPE is larger indicating less error, which is a good thing. Alpha =0.7 is preferfed, because the MAPE is larger indicating more error, which is a good thing. Step 3 of 5: Using a smoothing constant (alpha) =0.7 and assuming F1=y, calculate the exponential smoothing forecasted value for =15. Round to 2 decimal places. 1 Point Consider the following time series representing the average number of points scored by teams in NBA games over a 14 -day period. Use this info to answer the questions below. - Special Text to paste properly into Excel. Step 1 of 5 : Using a smoothing constant (alpha) =0.1 and assuming F1=1. calculate the exponential smoothing forecasted value for t=15 Round to 2 decimal places: Step 4 of 5: Calculate the MAPE (Mean Absolute Percent Error) for the Simple Exponential Smoothing forecasts for alpha = 0.7 that you calculated for time periods t=1 thru 14 in step 3 . Do NOT include the forecast for t=15, Express as a percent and round your answer to one decimal place (that is, 0.125 or 12.5% should be entered as 12.5). Step 2 of 5: Calculate the MAPE (Mean Absolute Percent Error) for the Simple Exponential Smoothing forecasts for alpha =0.1 that you generated for time periods t=1 thru 14 in step 1 . Do NOT include the forecast for t=15. Express as a percent and round your answer to one decimal place (that is, 0.125 or 12.5% should be entered as 12.5). Step 5 of 5: Considering the two MAPE values from the alpha =0.1 forecasts and the alpha =0.7 forecasts, which smoothing constant is preferted and why? Answer 0.5 Points Alpha =0,1 is preferred, because the MAPE is smaller indicating more error, which is a good thing. Alpha = 0.1 is preferred, becouse the MApe is smaller indicating less error, which is a good thing. Alpha =0.7 is preferred, because the MAPE is larger indicating less error, which is a good thing. Alpha =0.7 is preferfed, because the MAPE is larger indicating more error, which is a good thing. Step 3 of 5: Using a smoothing constant (alpha) =0.7 and assuming F1=y, calculate the exponential smoothing forecasted value for =15. Round to 2 decimal places. 1 Point

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