In situations where you need to compare forecasting methods for different time periods, the most appropriate...
In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is
a. ME
b. MSE
c. MAPE
d. MAE
Homework Answers
In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is MAPE.
MAPE is mean absolute percentage error. It helps in representing the rate of accuracy in the forecasting method in the different time periods, thereby conducting the comparison.
Answer: Option c
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In situations where you need to compare forecasting methods for
different time periods, the most appropriate...
Question: Look at the Rankings Worksheet. The manager has reviewed 3 different Forecasting methods and calculated...
Question: Look at the Rankings Worksheet. The manager has reviewed 3 different Forecasting methods and calculated the Mean Error (Not MAD), MSE and MAPE to evaluate the 3 different methods. Explain the value of using the Mean Error instead of the MAD! 3 different methods chosen ME RMSE MAPE Rank Regression 20876 119540 3.30% HW Additive 4222 102288 2.60% HW Multiplicative 895 78353 1.91% Mean Error, but not MAD MSE MAPE
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...
Before implementing a forecasting model is it important to Question 8 options: A. Utilize an alternative...
Before implementing a forecasting model is it important to Question 8 options: A. Utilize an alternative source of data to generate the actual forecasts. B. Make sure that you have found the model with the largest MAE. C. Rerun the model on the entire series (training+validation) in order to utilize the most recent data in generating your forecasts D. Rerun the model using the validation period only in order to avoid using ‘old’ data. Question 9 (1 point) Using the...
use the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week...
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...
business analytics Consider the following gasoline sales time series. If needed, round your answers to two-decimal...
business analytics
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week Sales (1,000s of gallons) (a) Show the exponential smoothing forecasts using a -0.1, and 0.2 Exponential Smoothing 9 = 0.1 0 = 0.2 Week (b) Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a 0.1 or 0 - 0.2 for the gasoline sales time series? An - Select your answer- smoothing constant provides the more accurate...
PLEASE ONLY ANSWER IF YOU CAN DO WHAT IS BLANK, I DON'T NEED HELP WITH WHAT...
PLEASE ONLY ANSWER IF YOU CAN DO WHAT IS BLANK, I DON'T NEED
HELP WITH WHAT IS FILLED OUT ALREADY. THANK YOU!
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6 Value 1914 16 10 17 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy: a. Mean absolute error (MAE) b. Mean squared error (MSE) c. Mean absolute percentage error...
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...
1. Comparing forecast models Aa Aa A statistician for the Boston Police Department developed forecasts of monthly armed robberies in Boston from June 1974 to May 1975 using two forecasting methods, m...
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Please help. I'm stuck. DATA: Gassins These data show the number of palons of gasoline sold...
Please help. I'm stuck.
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...
An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a...
An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is F. 127191, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy of MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.)...
Question: Look at the Rankings Worksheet. The manager has reviewed 3 different Forecasting methods and calculated the Mean Error (Not MAD), MSE and MAPE to evaluate the 3 different methods. Explain the value of using the Mean Error instead of the MAD! 3 different methods chosen ME RMSE MAPE Rank Regression 20876 119540 3.30% HW Additive 4222 102288 2.60% HW Multiplicative 895 78353 1.91% Mean Error, but not MAD MSE MAPE
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...
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...
business analytics
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits. Week Sales (1,000s of gallons) (a) Show the exponential smoothing forecasts using a -0.1, and 0.2 Exponential Smoothing 9 = 0.1 0 = 0.2 Week (b) Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a 0.1 or 0 - 0.2 for the gasoline sales time series? An - Select your answer- smoothing constant provides the more accurate...
PLEASE ONLY ANSWER IF YOU CAN DO WHAT IS BLANK, I DON'T NEED
HELP WITH WHAT IS FILLED OUT ALREADY. THANK YOU!
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6 Value 1914 16 10 17 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy: a. Mean absolute error (MAE) b. Mean squared error (MSE) c. Mean absolute percentage error...
1. Comparing forecast models Aa Aa A statistician for the Boston Police Department developed forecasts of monthly armed robberies in Boston from June 1974 to May 1975 using two forecasting methods, model A and model B. His forecasts, absolute forecast errors, and squared forecast errors for both forecasting techniques, along with the actual time series, are displayed in the following table. The time series plot of the data is shown under the table. (Data source: Time Series Data Library.) Model...
Please help. I'm stuck.
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...
An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is F. 127191, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy of MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.)...
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