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## Model For Forecasting Accuracy Assignment

Order ID:89JHGSJE83839Style:APA/MLA/Harvard/ChicagoPages:5-10

Instructions:Model For Forecasting Accuracy Assignment

1.Which of the following is not a good measure of forecast accuracy?

A) MSE – Mean sum of errors

B) MAE – Mean absolute value of errors

C) MAPE – Mean absolute percentage errors

D) RMSE – square root of mean squared errors

2.The most complicated forecasting model is always the best model for forecasting accuracy.

A) True

B) False

3.Forecast errors for regression models are the same as the fitted values of the regression

equation.

A) True

B) FalseModel For Forecasting Accuracy Assignment

4.Suppose you have the following regression equation where PROD = output produced per

month, LHR = labor hours paid per month, and QUAL = quality of raw materials purchased

within the month, and T=trend variable:Prod = ß0 + ß1LHR + ß2QUAL + ß3T. If ß3 = 3.5 and is

significantly different from zero, this result indicates

A) an increase in labor efficiency.

B) an increase in the quality of raw materials used in the production process.

C) an increase in labor efficiency or the quality of raw materials or both.

D) an increase in production efficiency holding constant labor efficiency and material quality.

E) an increase in production efficiency due to an increase in labor efficiency or quality of

materials or both.

5.Suppose you have the following regression equation where SALES = 100s of cars sold per

month, PRICE = average actual price paid by customer for car purchases in month, ADV =

monthly advertising expenses, SEPT = dummy variable with value 1 for Sept and 0 for all other

months; and FEB = dummy variable with value of 1 for February and 0 for all other months:

Sales = ß0 + ß1Price + ß2Adv + ß3Sept + ß4Feb. If ß3 = 3.5 and is significantly different from

zero, this result indicates that

A) sales are higher in September than in all other months.

B) sales are higher than sales in all other months excluding February. 6.What are the limitation of using regression analysis as a forecast tool?

A) Use of historical data may be limited in forecasting future.

B) Use of all available data may be good because one has much information to develop a good

model, but may be bad because a number of changes may have occurred over the time period of

the data.

C) Regression forecasts for future periods require information about future values of independent

variables.

D) Variation in the independent variables only capture limited amount of variability in dependent

variable.

E) All of the above

7.Moving average forecasts for period t is simply the average of the k previous observations in

the time series.

A) True

B) False

8.If one uses moving averages to make forecasts when there is an upward trend in the data,

moving averages will underestimate (under-forecast) future outcomes.

A) True

B) False

9.Exponential smoothing may be a better forecasting model than moving average models

because it puts greater weight on more recent data than historic data.

A) True

B) False

10.If one uses simple exponential smoothing models to make forecasts when there is an upward

trend in the data, simple exponential smoothing models will underestimate (under-forecast)

future outcomes.

A) True

B) False172

1.Which of the following is not a good measure of forecast accuracy?

A) MSE – Mean sum of errors

B) MAE – Mean absolute value of errors

C) MAPE – Mean absolute percentage errors

D) RMSE – square root of mean squared errors

2.The most complicated forecasting model is always the best model for forecasting accuracy.

A) True

B) False

3.Forecast errors for regression models are the same as the fitted values of the regression

equation.

A) True

B) False

4.Suppose you have the following regression equation where PROD = output produced per

month, LHR = labor hours paid per month, and QUAL = quality of raw materials purchased

within the month, and T=trend variable:Prod = ß0 + ß1LHR + ß2QUAL + ß3T. If ß3 = 3.5 and is

significantly different from zero, this result indicates

A) an increase in labor efficiency.

B) an increase in the quality of raw materials used in the production process.

C) an increase in labor efficiency or the quality of raw materials or both.

D) an increase in production efficiency holding constant labor efficiency and material quality.

E) an increase in production efficiency due to an increase in labor efficiency or quality of

materials or both.

5.Suppose you have the following regression equation where SALES = 100s of cars sold per

month, PRICE = average actual price paid by customer for car purchases in month, ADV =

monthly advertising expenses, SEPT = dummy variable with value 1 for Sept and 0 for all other

months; and FEB = dummy variable with value of 1 for February and 0 for all other months:

Sales = ß0 + ß1Price + ß2Adv + ß3Sept + ß4Feb. If ß3 = 3.5 and is significantly different from

zero, this result indicates that

A) sales are higher in September than in all other months.

B) sales are higher than sales in all other months excluding February. 6.What are the limitation of using regression analysis as a forecast tool?

A) Use of historical data may be limited in forecasting future.

B) Use of all available data may be good because one has much information to develop a good

model, but may be bad because a number of changes may have occurred over the time period of

the data.

C) Regression forecasts for future periods require information about future values of independent

variables.

D) Variation in the independent variables only capture limited amount of variability in dependent

variable.

E) All of the above

7.Moving average forecasts for period t is simply the average of the k previous observations in

the time series.

A) True

B) False

8.If one uses moving averages to make forecasts when there is an upward trend in the data,

moving averages will underestimate (under-forecast) future outcomes.

A) True

B) False

9.Exponential smoothing may be a better forecasting model than moving average models

because it puts greater weight on more recent data than historic data.

A) True

B) False

10.If one uses simple exponential smoothing models to make forecasts when there is an upward

trend in the data, simple exponential smoothing models will underestimate (under-forecast)

future outcomes.

A) True

B) FalseModel For Forecasting Accuracy Assignment

RUBRIC

Excellent Quality95-100%

Introduction45-41 points

The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.

Literature Support91-84 points

The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.

Methodology58-53 points

Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met.

Average Score50-85%

40-38 points

More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided.

83-76 points

Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration.

52-49 points

Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met.

Poor Quality0-45%

37-1 points

The background and/or significance are missing. No search history information is provided.

75-1 points

Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration.

48-1 points

There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met

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