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business analytics Consider the following gasoline sales time series. If needed, round your answers to two-decimal...
use the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week Sales (1,000s of gallons) 0.1, and a -0.2. (a) Show the exponential smoothing forecasts using a Exponential Smoothing Week a = 0.1 -0.2 (b) Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a 0.1 or 0.2 for the gasoline sales time series? An - Select your answer- smoothing constant provides the more accurate forecast, with an overall MSE...
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week Sales (1,000s of gallons) 1 17 2 21 3 16 4 24 5 17 6 18 7 22 8 20 9 21 10 19 11 16 12 25 (a) Show the exponential smoothing forecasts using α = 0.1, and α = 0.2. Exponential Smoothing Week α = 0.1 α = 0.2 13 (b) Applying the MSE measure of forecast accuracy, would you prefer a...
GASOLINE SALES TIME SERIES Sales (1000s of gallons) Week 21 19 5 18 6 16 7 20 18 22 10 20 11 15 12 22 show the exponential smoothing forecasts using a = 0.1 a. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a 2 for the gasoline sales time series (to 2 decimals)? .1 or a MSE for a = 1 MSE for a = 2 Select b. Are the results the same...
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DATA: Gassins These data show the number of palons of gasoline sold by a gasoline distributor in Bennington, Vermont, over Week Sales (1.000s of gallons) 1 17 21 N 3 19 4 22 5 18 6 16 2 20 8 18 9 22 10 20 11 15 12 22 Show the exponential smoothing forecasts using a=0.1. (Round your answers to two decimal places.) Time Series Value Forecast Week 1 17 2. 21 19 23 5 18...
The options for prefer for A B and C are
0.1 or 0.2
With the gasoline time series data from the given table, show the exponential smoothing forecasts using a = 0.1. GASOLINE SALES TIME SERIES Week 1 2 3 4 5 6 7 8 9 10 11 12 Sales (1000s of gallons) 17 21 19 23 18 16 20 18 22 20 15 22 a. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of...
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Consider the following time series data. Week 1 N 3 4 5 6 Value 19 11 13 10 14 12 (a) Construct a time series plot. 20 18 20 18 14 12 10 Week 3 4 Week D 20 18+ 16 Time Series Value Time Series Value 5 Week 0 Wook What type of pattem exists in the data? The data appear to follow a cyclical pattern. The data appear to follow a trend pattem. The data appear...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 11 16 1017 15 (a) Construct a time series plot. 20 20 20 18 16 14 12 10 c 14 12 12 0 23 4 5 67 0 23 4 5 67 Week Weck Week 20 18 0 1 2345 6 7 Week What type of pattern exists in the data? The data appear to follow a seasonal pattern. The data appear to follow a...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 13 16 12 18 14 a. Which of the following is a correct time series plot for this data? - Select your answer -plot #1plot #2plot #3Item 1 What type of pattern exists in the data? - Select your answer -VerticalHorizontalScatterItem 2 b. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week (to 2 decimals if necessary)....
Homework Consider the following time series data. Week Value a. Which of the following is a correct time series plot for this data? 1 18 2 14 3 17 4 12 5 17 6 15 TimeSeries Value 115 Week TimeSeries Value 3 4 5 Week 2 TimeSeries Value 15 3 4 . 5 Week plot #1 What type of pattern exists in the data? Horizontal a Search this course mework Week plot 01 What type of pattern exists in the...
Consider the following time series data Week 1 2 3 4 5 6 Value 19 14 16 12 18 15 a. Which of the following is a correct time series plot for this data? 1 Time eries Value 15 10 Week 2 TimeSeries Value 15 10 5 Week 4 3 TimeSeries Value 15 10 -5 Week 4 5 Select your answer What type of pattern exists in the data? What type of pattern exists in the data? Horizontal b. Develop...