Question

Calculate the MAPE for your forecast series using the values for year 2 through year 7....

Calculate the MAPE for your forecast series using the values for year 2 through year 7.

Year CP Forecast
1 $12.96
2 $14.31 $12.96
3 $15.34 $14.31
4 $15.49 $15.34
5 $15.70 $15.49
6 $16.00 $15.70
7 $15.62 $16.00
8 $15.62
Business   Finance   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

Calculation of MAPE :

CP Forecast CP-Forcast/CP*100
14.31 12.96 14.31-12.96/14.31*100=9.43%
15.34 14.31 15.34-14.31/15.34*100=6.71%
15.49 15.34 15.49-15.34/15.49*100=0.97%
15.70 15.49 15.70-15.49/15.70*100=1.34%
16.00 15.70 16-15.7/16*100=1.87%
15.62 16.00 15.62-16/15.62*100=2.43%
Total 22.75%

*While calculating CP-Forecast/CP*100, take the ABSOLUTE values.That means in the seventh year even 15.62-16/15.62*100 is -2.43% we have to consider as 2.43%

MAPE = 1/n*Total of (CP-Forcast/CP)*100

n =6 years

MAPE = 1/6*22.75%

= 3.79%

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for periods 3 through 10. Use the value for the first period as the forecast for the second period. Compute forecasts using α = 0.8. Compute the MAD and MSE. Time period Value 1 27 2 31 3 58 4 63 5 59 6 66 7 71 8 86 9 101 10 97
Consider the accompanying time series. a. Forecast the demand for each quarter in Year 4 using...
Consider the accompanying time series. a. Forecast the demand for each quarter in Year 4 using multiplicative decomposition. b. Interpret the meaning of the seasonal components. c. Calculate the MAD for this forecast. Year_1_Quarter   Year_ 1_Demand   Year_2_Quarter   Year_2_Demand   Year_3_Quarter   Year_3_Demand 1 4 1 5 1 8 2 10 2 13 2 16 3 11    3 11 3 14 4 5 4 9 4    8 .
The following times series shows the demand for a particular product over the past 10 months....
The following times series shows the demand for a particular product over the past 10 months. Month Value 1 324 2 311 3 303 4 314 5 323 6 313 7 302 8 315 9 312 10 326 a. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE, MAPE and a forecast for month 11. b. Calculate MSE and MAPE for three month moving average ? c. Compare the three-month moving average forecast...
Using a five-year moving average, compute MSE and a forecast for the year 11, for the...
Using a five-year moving average, compute MSE and a forecast for the year 11, for the following times series. MSE= yhat_11= Year Value Forecast Error Error^2 1 324 2 378 3 401 4 390 5 425 6 449 7 456 8 412 9 525 10 436
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 18 12 18 23 15 b. Develop the three-month moving average forecasts for this time series. Compute MSE and a forecast for month 8 (to 2 decimals if necessary). Enter negative values as negative number. Month Time Series Value Forecast Forecast Error Squared Forecast Error 1 24 2 13 3 18 4 12 ? ? ? 5 18 ? ? ? 6 23...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for periods 3 through 10. Use the value for the first period as the forecast for the second period. Compute forecasts using α = 0.1. Compute the MAD and MSE. Time period Value 1 27 2 31 3 58 4 63 5 59 6 66 7 71 8 86 9 101 10 97 Group of answer choices A) MAD=296.6, MSE=1266.5 B) MAD=296.6 , MSE=11398.5 C)...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for periods 3 through 10. Use the value for the first period as the forecast for the second period. Compute forecasts using α = 0.8. Compute the MAD and MSE. Time period Value 1 27 2 31 3 58 4 63 5 59 6 66 7 71 8 86 9 101 10 97 Group of answer choices a) MAD=9.7, MSE=1585.6 b) MAD=9.7, MSE=176.2 c) MAD=10.2,...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12 15 11 17 15 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 forecast for the...
Considering the following time series data: Week 1 2 3 4 5 6 7 8 9...
Considering the following time series data: Week 1 2 3 4 5 6 7 8 9 10 Sales 8 11 14 19 16 10 8 12 14 16 Compute the naïve forecast and the three-week Moving Average and evaluate the forecast accuracy considering the Mean Absolute Error (MAE), Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE) for each of these two predictions. Compare both of them and determine which is the best model
1. Using the data below, what is the value of RMSE? Week Time Series Value Forecast...
1. Using the data below, what is the value of RMSE? Week Time Series Value Forecast 1 3 7.00 2 5 4.00 3 2 5.00 4 8 8.00 2. Using the data below, calculate the squared error for the 4th week. Use the 2 period moving average to create the forecast. Week Time Series Value 1 19.00 2 11.00 3 22.00 4 7.00 Please, do the all the work and show processes
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT