Given the following data, compute the MAE for the forecasts. Round your answer to two decimal...
Given the following data, compute the MAE for the forecasts. Round your answer to two decimal places. For example, if your answer is 3, enter 3.00. Year Actual Demand Forecast 2001 16 21 2002 19 19 2003 18 22 Your Answer: Question 23 options:
Homework Answers
Year Actual demand Forecast Forecast error Absolute value of forecast error
2001 16 21 -5 5
2002 19 19 0 0
2003 18 22 -4 4
Total 9
MAE = Total absolute forecast error / n
= 9 / 3
= 3
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Given the following data, compute the MAE for the forecasts.
Round your answer to two decimal...
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...
Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in...
Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in Bennington, Vermont, over the past 12 weeks. Week Sales (1,000s of gallons) 1 17 2 22 3 20 4 24 5 18 6 17 7 21 8 19 9 23 10 21 11 16 12 22 (a) Compute four-week and five-week moving averages for the time series. Week Time Series Value 4-Week Moving Average Forecast 5-Week Moving Average Forecast 1 17 2 22 3...
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...
please i need asap answer 1. Given the data below, compute for the following: a) Forecasts...
please i need asap
answer
1. Given the data below, compute for the following: a) Forecasts for P5 to P12 using a 4-period simple moving average b) Forecasts for P5 to P12 using a 4-month weighted moving average with the following weights: Most recent period = 0.40 2nd most recent period = 0.30 3rd most recent period = 0.20 4th most recent period = 0.10 Assuming a forecast of 5,000 units for Period 4 and a = 0.30, compute for...
The options for prefer for A B and C are 0.1 or 0.2 With the gasoline...
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...
Ch8-A For data of weekly returns (in %) of Google stock given here, forecast the return for the w...
Ch8-A For data of weekly returns (in %) of Google stock given here, forecast the return for the week of March 5, 2017 as follows. [Note: Express your forecasts in % rounded to to 2 decimal places (eg, 3.23%), and express the MSE's and MAE rounded to 5 decimal places (e.g., 0.00073).] (a) Use a 3-week moving average and find the MSE and MAE. (b) Use exponential smoothing with alpha value 0.3 and compute the error measures (c) Now using...
Following are two weekly forecasts made by two different methods for the number of gallons of...
Following are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons Week Week Forecast Method 1 0.95 1.02 0.92 1 17 Actual Demand 0.72 100 107 Forecast Method 2 0.82 120 Actual Demand 0.72 092 1.11 107 1.00 1.00 The MAD for Method 1 - thousand gallons (round your response to the decimal places) Enter your...
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6...
Problem 15-03 (Algorithmic) Consider the following time series data. Week 1 2 3 4 5 6 Value 18 14 16 11 17 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy: Mean absolute error (MAE) Mean squared error (MSE) Mean absolute percentage error (MAPE) Round your answers to two decimal places. MAE = MSE = MAPE = Using the average of all the historical data as a...
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 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...
please i need asap
answer
1. Given the data below, compute for the following: a) Forecasts for P5 to P12 using a 4-period simple moving average b) Forecasts for P5 to P12 using a 4-month weighted moving average with the following weights: Most recent period = 0.40 2nd most recent period = 0.30 3rd most recent period = 0.20 4th most recent period = 0.10 Assuming a forecast of 5,000 units for Period 4 and a = 0.30, compute for...
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...
Ch8-A For data of weekly returns (in %) of Google stock given here, forecast the return for the week of March 5, 2017 as follows. [Note: Express your forecasts in % rounded to to 2 decimal places (eg, 3.23%), and express the MSE's and MAE rounded to 5 decimal places (e.g., 0.00073).] (a) Use a 3-week moving average and find the MSE and MAE. (b) Use exponential smoothing with alpha value 0.3 and compute the error measures (c) Now using...
Following are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons Week Week Forecast Method 1 0.95 1.02 0.92 1 17 Actual Demand 0.72 100 107 Forecast Method 2 0.82 120 Actual Demand 0.72 092 1.11 107 1.00 1.00 The MAD for Method 1 - thousand gallons (round your response to the decimal places) Enter your...
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...
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