Assignment Prompt & Instructions
will need toight if possible
– 2 years ago
**files (2)**
– ## project_description.docx
– ## BUSA511_individual_project_template1.docx
**## project_description.docx**
**Project Assignment BUSA 511, Business Analytics for Managers**
**The case**
Considering monthly demands for the ABC Corporation as shown below.
**Question**
Forecast the monthly demands for Year 6 using
**moving average**,
**simple exponential smoothing**,
**Holts' model**, and
**Winter's model**. In each case, evaluate the bias, TS, MAD, MAPE, and MSE.
**Project Assignment Guidance**
1. To answer the question above, firstly based on the monthly sales data of Year 1, 2, 3, 4 and 5, you should forecast the 12 monthly demands of Year 6 from January to December using "
**_moving average"_**, "
**_simple exponential smoothing"_**, "
**_Holts' model_**", and "
**_Winter's model”, respectively_**. Secondly, you should calculate the forecast-error indicators of bias, TS, MAD, MAPE, and MSE regarding these four models. Thirdly, based on your findings, you should identify the best forecasting methods and provide your justifications.
2. Two documents should be submitted for this assignment.
**The first** is the Excel file in which the formula, the calculation processes and solutions of the four forecasting methods, and the related forecast-error estimates of bias, TS, MAD, MAPE, and MSE should be given.
**The second** is the word file template as report by answering questions asked in the report template. This word file template will be posted on D2L.
**_(_**
**_Note: Sample of the work in excel and Video recording of the tutorial is posted on D2L)_**
3. The mark weighting of the analysis of the above four forecasting methods will be listed in the report template posted on D2L.
4. The submission deadline is stated on D2L page for the course.
5. You should submit e-copy of your assignment (word-format report with Excel file(s), through the submission portal on D2L (no hard copy needed)
2
**image1.emf**
**## BUSA511_individual_project_template1.docx**
**BUSA 511: Project Assignment cover page**
Assignment for Course: BUSA 511: Business Analytics for Managers
Submitted to: Dr. Syed A. Raza
Submitted by:
| | |
| — | — |
| **Student Name** | **CWID** |
| | |
:
Title of Assignment:
**Time Series Forecasting Group Project**
CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance received in its preparation is fully acknowledge and disclosed in the paper. I have also cited any sources from which we used data, ideas of words, whether quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course
\*\*\*****************************************
**Time Series Forecasting Project Instructions**
**_Instructions_**
This is an individual assignment and therefore must be completed by an individual student without outside assistance of any type. Follow the instructions below in order to complete the assignment:
·
**Step 1**: Download and read the project statement for the
_on the Forecasting problem_ stated in the Microsoft Word file “
**project_description.docx**”. Read carefully this document
·
**Step 2**: Download the Excel file “
**project_data.xlsx**”. Use the data in the file to perform timeseries forecasting analyses.
·
**Step 3**: Based on your analytics performed and use of the models in Step 2, answer the questions and provide a short (
_not exceeding 500 words_) recommendation/explanation
**_Submittals_**
1. Submit your answers to this assignment using this Microsoft Word document and post to the assignment drop box before the required deadline. Be sure to complete the above first page cover sheet. Enter your answers in the pages below to include all of your answers and results of your interpretations of calculations for the assignment questions. Your answers must be entered directly into this Word document below each question. Use as much space as needed.
2. Submit your Excel spreadsheet(s) with calculations/ visualizations to the assignment drop box before the required deadline. Your Excel model calculations will be used to substantiate your answers to the assignment questions herein.
**_Grading_**
This is an individual assignment. A total of 100 percentage points is possible for this assignment. This includes the point values which are assigned to each question – point values are noted next to each question below. Use APA 7 writing style as a guide for answers that require a written explanation. Up to 10 points will be deducted from the combination of written explanation answers that are poorly written. The percentage points earned on this assignment will be 20% weight obtain the final assignment grade.
Please answer following Question with reference to the project file: “
**Project_description.docx**”
**_Question 1_** (6 points): Define a problem statement which reflects the challenge faced in this prediction problem (
_Do not exceed 500 words_)
**Answer**:
**_Question 2_** (6 points): Develop a 3-period moving average forecasting model. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words_)
**Answer**:
**_Question 3_** (6 points): Compute for the model developed in Question 2, compute the error parameters MAD, MSE, MAPE, and TS. Explain these error computations (
_Explanation NOT to exceed 500 words_)
**Answer**:
**_Question 4_** (6 points): Develop a simple exponential smoothing forecasting model, assume, =0.2. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 5_** (6 points): For the model developed in Question 4, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 6_** (6 points): For the model developed in Question 4, using Excel Solver optimize the value of with and objective to minimize MSE. Report your results provide a discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 7_** (6 points): Develop a Holt’s model for forecasting, assume, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 8_** (6 points): For the model developed in Question 7, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 9_** (6 points): For the model developed in Question 7, using Excel Solver optimize the values of and with an objective to minimize MAD. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 10_** (6 points): Develop a Winter’s model for forecasting, assume, =0.2, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 11_** (6 points): For the model developed in Question 10, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 12_** (6 points): For the model developed in Question 10, using Excel Solver optimize the values of , , and with an objective to minimize MAPE. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 13_** (6 points): Discuss the model developed in Question 10 is how different from model developed in Question 7, (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 14_** (22 points): Which model you will select and Why and how does the optimization improve the forecasting performance of the methods? (
_1 to 2-page discussion recommend_)
1
**image1.png**
**## BUSA511_individual_project_template1.docx**
**BUSA 511: Project Assignment cover page**
Assignment for Course: BUSA 511: Business Analytics for Managers
Submitted to: Dr. Syed A. Raza
Submitted by:
| | |
| — | — |
| **Student Name** | **CWID** |
| | |
:
Title of Assignment:
**Time Series Forecasting Group Project**
CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance received in its preparation is fully acknowledge and disclosed in the paper. I have also cited any sources from which we used data, ideas of words, whether quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course
\*\*\*****************************************
**Time Series Forecasting Project Instructions**
**_Instructions_**
This is an individual assignment and therefore must be completed by an individual student without outside assistance of any type. Follow the instructions below in order to complete the assignment:
·
**Step 1**: Download and read the project statement for the
_on the Forecasting problem_ stated in the Microsoft Word file “
**project_description.docx**”. Read carefully this document
·
**Step 2**: Download the Excel file “
**project_data.xlsx**”. Use the data in the file to perform timeseries forecasting analyses.
·
**Step 3**: Based on your analytics performed and use of the models in Step 2, answer the questions and provide a short (
_not exceeding 500 words_) recommendation/explanation
**_Submittals_**
1. Submit your answers to this assignment using this Microsoft Word document and post to the assignment drop box before the required deadline. Be sure to complete the above first page cover sheet. Enter your answers in the pages below to include all of your answers and results of your interpretations of calculations for the assignment questions. Your answers must be entered directly into this Word document below each question. Use as much space as needed.
2. Submit your Excel spreadsheet(s) with calculations/ visualizations to the assignment drop box before the required deadline. Your Excel model calculations will be used to substantiate your answers to the assignment questions herein.
**_Grading_**
This is an individual assignment. A total of 100 percentage points is possible for this assignment. This includes the point values which are assigned to each question – point values are noted next to each question below. Use APA 7 writing style as a guide for answers that require a written explanation. Up to 10 points will be deducted from the combination of written explanation answers that are poorly written. The percentage points earned on this assignment will be 20% weight obtain the final assignment grade.
Please answer following Question with reference to the project file: “
**Project_description.docx**”
**_Question 1_** (6 points): Define a problem statement which reflects the challenge faced in this prediction problem (
_Do not exceed 500 words_)
**Answer**:
**_Question 2_** (6 points): Develop a 3-period moving average forecasting model. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words_)
**Answer**:
**_Question 3_** (6 points): Compute for the model developed in Question 2, compute the error parameters MAD, MSE, MAPE, and TS. Explain these error computations (
_Explanation NOT to exceed 500 words_)
**Answer**:
**_Question 4_** (6 points): Develop a simple exponential smoothing forecasting model, assume, =0.2. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 5_** (6 points): For the model developed in Question 4, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 6_** (6 points): For the model developed in Question 4, using Excel Solver optimize the value of with and objective to minimize MSE. Report your results provide a discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 7_** (6 points): Develop a Holt’s model for forecasting, assume, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 8_** (6 points): For the model developed in Question 7, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 9_** (6 points): For the model developed in Question 7, using Excel Solver optimize the values of and with an objective to minimize MAD. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 10_** (6 points): Develop a Winter’s model for forecasting, assume, =0.2, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 11_** (6 points): For the model developed in Question 10, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 12_** (6 points): For the model developed in Question 10, using Excel Solver optimize the values of , , and with an objective to minimize MAPE. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 13_** (6 points): Discuss the model developed in Question 10 is how different from model developed in Question 7, (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 14_** (22 points): Which model you will select and Why and how does the optimization improve the forecasting performance of the methods? (
_1 to 2-page discussion recommend_)
1
**image1.png**
**## project_description.docx**
**Project Assignment BUSA 511, Business Analytics for Managers**
**The case**
Considering monthly demands for the ABC Corporation as shown below.
**Question**
Forecast the monthly demands for Year 6 using
**moving average**,
**simple exponential smoothing**,
**Holts' model**, and
**Winter's model**. In each case, evaluate the bias, TS, MAD, MAPE, and MSE.
**Project Assignment Guidance**
1. To answer the question above, firstly based on the monthly sales data of Year 1, 2, 3, 4 and 5, you should forecast the 12 monthly demands of Year 6 from January to December using "
**_moving average"_**, "
**_simple exponential smoothing"_**, "
**_Holts' model_**", and "
**_Winter's model”, respectively_**. Secondly, you should calculate the forecast-error indicators of bias, TS, MAD, MAPE, and MSE regarding these four models. Thirdly, based on your findings, you should identify the best forecasting methods and provide your justifications.
2. Two documents should be submitted for this assignment.
**The first** is the Excel file in which the formula, the calculation processes and solutions of the four forecasting methods, and the related forecast-error estimates of bias, TS, MAD, MAPE, and MSE should be given.
**The second** is the word file template as report by answering questions asked in the report template. This word file template will be posted on D2L.
**_(_**
**_Note: Sample of the work in excel and Video recording of the tutorial is posted on D2L)_**
3. The mark weighting of the analysis of the above four forecasting methods will be listed in the report template posted on D2L.
4. The submission deadline is stated on D2L page for the course.
5. You should submit e-copy of your assignment (word-format report with Excel file(s), through the submission portal on D2L (no hard copy needed)
2
**image1.emf**
**## BUSA511_individual_project_template1.docx**
**BUSA 511: Project Assignment cover page**
Assignment for Course: BUSA 511: Business Analytics for Managers
Submitted to: Dr. Syed A. Raza
Submitted by:
| | |
| — | — |
| **Student Name** | **CWID** |
| | |
:
Title of Assignment:
**Time Series Forecasting Group Project**
CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance received in its preparation is fully acknowledge and disclosed in the paper. I have also cited any sources from which we used data, ideas of words, whether quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course
\*\*\*****************************************
**Time Series Forecasting Project Instructions**
**_Instructions_**
This is an individual assignment and therefore must be completed by an individual student without outside assistance of any type. Follow the instructions below in order to complete the assignment:
·
**Step 1**: Download and read the project statement for the
_on the Forecasting problem_ stated in the Microsoft Word file “
**project_description.docx**”. Read carefully this document
·
**Step 2**: Download the Excel file “
**project_data.xlsx**”. Use the data in the file to perform timeseries forecasting analyses.
·
**Step 3**: Based on your analytics performed and use of the models in Step 2, answer the questions and provide a short (
_not exceeding 500 words_) recommendation/explanation
**_Submittals_**
1. Submit your answers to this assignment using this Microsoft Word document and post to the assignment drop box before the required deadline. Be sure to complete the above first page cover sheet. Enter your answers in the pages below to include all of your answers and results of your interpretations of calculations for the assignment questions. Your answers must be entered directly into this Word document below each question. Use as much space as needed.
2. Submit your Excel spreadsheet(s) with calculations/ visualizations to the assignment drop box before the required deadline. Your Excel model calculations will be used to substantiate your answers to the assignment questions herein.
**_Grading_**
This is an individual assignment. A total of 100 percentage points is possible for this assignment. This includes the point values which are assigned to each question – point values are noted next to each question below. Use APA 7 writing style as a guide for answers that require a written explanation. Up to 10 points will be deducted from the combination of written explanation answers that are poorly written. The percentage points earned on this assignment will be 20% weight obtain the final assignment grade.
Please answer following Question with reference to the project file: “
**Project_description.docx**”
**_Question 1_** (6 points): Define a problem statement which reflects the challenge faced in this prediction problem (
_Do not exceed 500 words_)
**Answer**:
**_Question 2_** (6 points): Develop a 3-period moving average forecasting model. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words_)
**Answer**:
**_Question 3_** (6 points): Compute for the model developed in Question 2, compute the error parameters MAD, MSE, MAPE, and TS. Explain these error computations (
_Explanation NOT to exceed 500 words_)
**Answer**:
**_Question 4_** (6 points): Develop a simple exponential smoothing forecasting model, assume, =0.2. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 5_** (6 points): For the model developed in Question 4, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 6_** (6 points): For the model developed in Question 4, using Excel Solver optimize the value of with and objective to minimize MSE. Report your results provide a discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 7_** (6 points): Develop a Holt’s model for forecasting, assume, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 8_** (6 points): For the model developed in Question 7, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 9_** (6 points): For the model developed in Question 7, using Excel Solver optimize the values of and with an objective to minimize MAD. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 10_** (6 points): Develop a Winter’s model for forecasting, assume, =0.2, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 11_** (6 points): For the model developed in Question 10, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 12_** (6 points): For the model developed in Question 10, using Excel Solver optimize the values of , , and with an objective to minimize MAPE. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 13_** (6 points): Discuss the model developed in Question 10 is how different from model developed in Question 7, (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 14_** (22 points): Which model you will select and Why and how does the optimization improve the forecasting performance of the methods? (
_1 to 2-page discussion recommend_)
1
**image1.png**
**## project_description.docx**
**Project Assignment BUSA 511, Business Analytics for Managers**
**The case**
Considering monthly demands for the ABC Corporation as shown below.
**Question**
Forecast the monthly demands for Year 6 using
**moving average**,
**simple exponential smoothing**,
**Holts' model**, and
**Winter's model**. In each case, evaluate the bias, TS, MAD, MAPE, and MSE.
**Project Assignment Guidance**
1. To answer the question above, firstly based on the monthly sales data of Year 1, 2, 3, 4 and 5, you should forecast the 12 monthly demands of Year 6 from January to December using "
**_moving average"_**, "
**_simple exponential smoothing"_**, "
**_Holts' model_**", and "
**_Winter's model”, respectively_**. Secondly, you should calculate the forecast-error indicators of bias, TS, MAD, MAPE, and MSE regarding these four models. Thirdly, based on your findings, you should identify the best forecasting methods and provide your justifications.
2. Two documents should be submitted for this assignment.
**The first** is the Excel file in which the formula, the calculation processes and solutions of the four forecasting methods, and the related forecast-error estimates of bias, TS, MAD, MAPE, and MSE should be given.
**The second** is the word file template as report by answering questions asked in the report template. This word file template will be posted on D2L.
**_(_**
**_Note: Sample of the work in excel and Video recording of the tutorial is posted on D2L)_**
3. The mark weighting of the analysis of the above four forecasting methods will be listed in the report template posted on D2L.
4. The submission deadline is stated on D2L page for the course.
5. You should submit e-copy of your assignment (word-format report with Excel file(s), through the submission portal on D2L (no hard copy needed)
2
**image1.emf**
**## BUSA511_individual_project_template1.docx**
**BUSA 511: Project Assignment cover page**
Assignment for Course: BUSA 511: Business Analytics for Managers
Submitted to: Dr. Syed A. Raza
Submitted by:
| | |
| — | — |
| **Student Name** | **CWID** |
| | |
:
Title of Assignment:
**Time Series Forecasting Group Project**
CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance received in its preparation is fully acknowledge and disclosed in the paper. I have also cited any sources from which we used data, ideas of words, whether quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course
\*\*\*****************************************
**Time Series Forecasting Project Instructions**
**_Instructions_**
This is an individual assignment and therefore must be completed by an individual student without outside assistance of any type. Follow the instructions below in order to complete the assignment:
·
**Step 1**: Download and read the project statement for the
_on the Forecasting problem_ stated in the Microsoft Word file “
**project_description.docx**”. Read carefully this document
·
**Step 2**: Download the Excel file “
**project_data.xlsx**”. Use the data in the file to perform timeseries forecasting analyses.
·
**Step 3**: Based on your analytics performed and use of the models in Step 2, answer the questions and provide a short (
_not exceeding 500 words_) recommendation/explanation
**_Submittals_**
1. Submit your answers to this assignment using this Microsoft Word document and post to the assignment drop box before the required deadline. Be sure to complete the above first page cover sheet. Enter your answers in the pages below to include all of your answers and results of your interpretations of calculations for the assignment questions. Your answers must be entered directly into this Word document below each question. Use as much space as needed.
2. Submit your Excel spreadsheet(s) with calculations/ visualizations to the assignment drop box before the required deadline. Your Excel model calculations will be used to substantiate your answers to the assignment questions herein.
**_Grading_**
This is an individual assignment. A total of 100 percentage points is possible for this assignment. This includes the point values which are assigned to each question – point values are noted next to each question below. Use APA 7 writing style as a guide for answers that require a written explanation. Up to 10 points will be deducted from the combination of written explanation answers that are poorly written. The percentage points earned on this assignment will be 20% weight obtain the final assignment grade.
Please answer following Question with reference to the project file: “
**Project_description.docx**”
**_Question 1_** (6 points): Define a problem statement which reflects the challenge faced in this prediction problem (
_Do not exceed 500 words_)
**Answer**:
**_Question 2_** (6 points): Develop a 3-period moving average forecasting model. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words_)
**Answer**:
**_Question 3_** (6 points): Compute for the model developed in Question 2, compute the error parameters MAD, MSE, MAPE, and TS. Explain these error computations (
_Explanation NOT to exceed 500 words_)
**Answer**:
**_Question 4_** (6 points): Develop a simple exponential smoothing forecasting model, assume, =0.2. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 5_** (6 points): For the model developed in Question 4, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 6_** (6 points): For the model developed in Question 4, using Excel Solver optimize the value of with and objective to minimize MSE. Report your results provide a discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 7_** (6 points): Develop a Holt’s model for forecasting, assume, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 8_** (6 points): For the model developed in Question 7, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 9_** (6 points): For the model developed in Question 7, using Excel Solver optimize the values of and with an objective to minimize MAD. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 10_** (6 points): Develop a Winter’s model for forecasting, assume, =0.2, =0.3, and =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 11_** (6 points): For the model developed in Question 10, compute the error parameters MAD, MSE, MAPE, and TS.
**Answer**:
**_Question 12_** (6 points): For the model developed in Question 10, using Excel Solver optimize the values of , , and with an objective to minimize MAPE. Report your results provide a Discussion how optimization improved the forecasting error (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 13_** (6 points): Discuss the model developed in Question 10 is how different from model developed in Question 7, (
_Discussion NOT to exceed 500 words)_
**Answer**:
**_Question 14_** (22 points): Which model you will select and Why and how does the optimization improve the forecasting performance of the methods? (
_1 to 2-page discussion recommend_)
1
**image1.png**