1. 2. 3. The following time series shows the sales of a particular product over the past 12 months. 4. DATA file 5. 6. 7. a. Construct a time series plot. A. 160 Sales 140 120 100 80 60 40 20 Month Sales Month Sales 1 105 7 145 2 135 8 140 3 120 9 100 4 105 10 80 5 90 11 100 6 120 2 12 110 Hint(s) Check My Work (2 remaining) B. 160 Sales C. 140 120 100 80 60 40 20 Month 6 8 10 12 Month 160 Sales 140 120 100 M 80 60 40 C. -160 Sales -140 120 100 D. 80- 60 40 20 2 4 6 8 10 12 Month 160 Sales 140 120 M 100 80 60 40 20 20 20 2 6 Month Time series plot B 8 00 10 12 What type of pattern exists in the data? Horizontal pattern b. Use = 0.3 to compute the exponential smoothing forecasts for the time series (to 2 decimals). Enter negative value as negative number. Do not round intermediate calculations. Time-Series Month Value 1 105 2 135 3 120 +1 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110 Forecast 00000000000 Forecast Error Error 00000000000 c. Use a smoothing constant of a = 0.5 to compute the exponential smoothing forecasts (to 2 decimals). Enter negative value as negative number. If your answer is zero enter "0". Do not round intermediate calculations. Time-Series Menth Value Feresact Forecast Error 12 110 c. Use a smoothing constant of a = 0.5 to compute the exponential smoothing forecasts (to 2 decimals). Enter negative value as negative number. If your answer is zero enter "0". Do not round intermediate calculations. Time-Series Month Value Forecast Forecast Error Error 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 6 100 10 80 11 100 12 110 00000000000 00000000000 00000000000 Compute MSE (to 2 decimals). Do not round intermediate calculations. MSE (a = 0.3) MSE (a = 0.5) Does a smoothing constant of 0.3 or 0.5 appear to provide more accurate forecasts based on MSE? - Select your answer -