Question

In: Other

using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data:

Week 1 2 3 4 5 6
Value 18 13 16 11 17 14

using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.
a. mean absolute error

b.mean squared error

c. mean absolute percentage error

d.What is the forecast for Week 7?

2. refer to the time series data in exercise 1. using the average of all the historical data as a forecast for the next period, compute the following measures of forecast accuracy

: a. mean absolute error

b. mean squared error

c. mean absolute percentage error

d. What is the forecast for Week 7?

3. exercises 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecasts for the historical data? explain.

Expert Solution

Amanda K answered 2 years ago

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy:

Consider the following time series data. Week123456Value201315111714Using the naïve 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 (MAPE) Round your answers to two decimal places. MAE = MSE = MAPE = Using the average of all the historical data as a forecast for the next period, compute the same three values. Round your answers to two decimal places. MAE = MSE = MAPE = Which method appears to...

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy:

Consider the following time series data. Week 1 2 3 4 5 6Value 19 12 16 10 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 next period, compute...

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data. Week 1 2 3 4 5 6 Value 19 13 15 10 17 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) Mean absolute error If required, round your answer to one decimal place. (b) Mean squared error If required, round your answer to one decimal place. (c) Mean absolute percentage error If required, round your intermediate calculations and final...

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data. Week 1 2 3 4 5 6 Value 18 12 16 11 17 14 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) Mean absolute error If required, round your answer to one decimal place. (b) Mean squared error If required, round your answer to one decimal place. (c) Mean absolute percentage error If required, round your intermediate calculations and final...

Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 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 (to 1 decimal). b.Mean squared error (to 1 decimal). c. Mean absolute percentage error (to 2 decimals). d. What is the forecast for week 7 (to 2 decimals)?

Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data. Week 1 2 3 4 5 6 Value 20 15 18 14 18 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 (to 1 decimal). _______ b.Mean squared error (to 1 decimal). _____ c. Mean absolute percentage error (to 2 decimals). _____% d. What is the forecast for week 7 (to 2 decimals)? ______

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Consider the following time series data: Week 1 2 3 4 5 6 -------------------------------------------------------------------------------------------------------- Value 18 13 16 11 17 14 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. A. mean absolute error B. mean squared error C. mean absolute percentage error d. What is the forecast for Week 7?

Using the naïve method (most recent value) as the forecast for the next year, what are...

Using the naïve method (most recent value) as the forecast for the next year, what are the following measures of forecast accuracy 1) Mean absolute error 2) Mean squared error 3) Mean absolute percentage error 4) What is the forecast for year 11? Consider the data below: Year Value 1 234 2 287 3 255 4 310 5 298 6 250 7 456 8 412 9 525 10 436 Options A. 1) 72.44 2) 8263.11 3) 18.86% 4) 436...

Use the Naïve Method of forecasting, prepare tables and calculate forecast accuracy measures. What is the forecast for month 11? Prepare the Time Series Plots.

Consider the following time series data. Month 1 2 3 4 5 6 7 8 9 10 Value 12 19 24 13 20 23 15 21 23 18 Use the Naïve Method of forecasting, prepare tables and calculate forecast accuracy measures. What is the forecast for month 11? Prepare the Time Series Plots. Use the “Historical Average Forecasting Method” that calculates “Forecast for a month” as “the average of all the observed data right from the beginning up...

Calculate the measures of forecast error using the naive (most recent value) method and the average of historical data (to 2 decimals).

Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 17 11 17 15 Calculate the measures of forecast error using the naive (most recent value) method and the average of historical data (to 2 decimals). Naive method Historical data Mean absolute error Mean squared error Mean absolute percentage error Top of Form Consider the following time series data. Month 1 2 3 4 5 6 7 Value 23 14 19 10 18 23...

Question

using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Solutions

Expert Solution

Related Solutions

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy:

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy:

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Using the naïve method (most recent value) as the forecast for the next year, what are...

Use the Naïve Method of forecasting, prepare tables and calculate forecast accuracy measures. What is the forecast for month 11? Prepare the Time Series Plots.

Calculate the measures of forecast error using the naive (most recent value) method and the average of historical data (to 2 decimals).