Homework Answers
Hot winter method is not suitable as thee is incrwsing treand independ of season.
Regression method would be better to use here as there linear treand in rise with less variation.
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Q7 We have observed the time series shown in the following line chart: 60 50 40...
TEST, I need Help A.S.A.P PLease!!! I need to submit this within the next hour and a half. It's...
1. Regression is always a superior forecasting method to exponential smoothing, so regression should be used whenever the appropriate software is available. (Points :1)TrueFalse2. Time-series models rely on judgment in an attempt to incorporate qualitative or subjective factors into the forecasting model. (Points : 1)TrueFalse3. A trend-projection forecasting method is a causal forecasting method. (Points : 1)TrueFalse4. Qualitative models attempt to incorporate judgmental or subjective factors into the forecasting model. (Points : 1)TrueFalse5. The naive forecast for the next period...
2. Consider the following time series data: 2Month Value 20 15 23 6 4 13 6 18 25 10 8 10 9 24 12 10 21 13 19 14 15...
2. Consider the following time series data: 2Month Value 20 15 23 6 4 13 6 18 25 10 8 10 9 24 12 10 21 13 19 14 15 la. Use a α # 0.25 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for Month 12. b. Compare the two-month moving average forecast with the exponential smoothing forecast using a 0.25. Which appears to 17 provide the better forecast based on MSE?...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 11 16 1017 15 (a) Construct a ...
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...
The following time series represents the hourly customer volume for a small dining establishment. Hour Customer...
The following time series represents the hourly customer volume for a small dining establishment. Hour Customer volume 7:00 a.m. 5 8:00 a.m. 5 9:00 a.m. 15 10:00 a.m. 20 11:00 a.m. 30 12:00 noon 50 1:00 p.m. 45 2:00 p.m. 30 3:00 p.m. 40 4:00 p.m. 20 5:00 p.m. 10 Use an exponential smoothing model with α = 0.50 to produce forecasts for this time series. Assume that the forecast for the 7:00 a.m. time slot is 5 customers. What recommendations...
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week...
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...
Please help Consider the following time series data. Week 1 N 3 4 5 6 Value...
Please help
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...
GASOLINE SALES TIME SERIES Sales (1000s of gallons) Week 21 19 5 18 6 16 7...
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...
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 24...
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 24 13 21 14 20 23 15 (c) Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for month 8. If required, round your answers to two decimal places. Do not round intermediate calculation. MSE: The forecast for month 8: (e) Use trial and error to find a value of the exponential smoothing coefficient α...
The following time series shows the number of units of a particular product sold over the...
The following time series shows the number of units of a
particular product sold over the past six months.
a. Use
= 0.2 to compute the exponential smoothing values for the time
series, forecast the sales volume for month 7, and fill in the
unknown spaces.
Compute the number (i):
Compute the number (ii):
Compute the number (iii):
What is the mean square error (MSE)?
b. Consider the following 3-month moving average for the above
time series and forecasting the...
Check my work 4 Click here for the Excel Data File Actual series are plotted along...
Check my work 4 Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 8.33 points 20 eBook 15 Hint 10 Print -Linear (y) Expon. (y) References 5 0 t 0 5 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Variable Linear Trend Exponential Trend Intercept t Standard Error Ch 4 Linear Trend...
2. Consider the following time series data: 2Month Value 20 15 23 6 4 13 6 18 25 10 8 10 9 24 12 10 21 13 19 14 15 la. Use a α # 0.25 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for Month 12. b. Compare the two-month moving average forecast with the exponential smoothing forecast using a 0.25. Which appears to 17 provide the better forecast based on MSE?...
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...
Please help
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...
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...
The following time series shows the number of units of a
particular product sold over the past six months.
a. Use
= 0.2 to compute the exponential smoothing values for the time
series, forecast the sales volume for month 7, and fill in the
unknown spaces.
Compute the number (i):
Compute the number (ii):
Compute the number (iii):
What is the mean square error (MSE)?
b. Consider the following 3-month moving average for the above
time series and forecasting the...
Check my work 4 Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 8.33 points 20 eBook 15 Hint 10 Print -Linear (y) Expon. (y) References 5 0 t 0 5 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Variable Linear Trend Exponential Trend Intercept t Standard Error Ch 4 Linear Trend...
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