Consider the following time series data

1. Consider the following time series data. (Use Excel for this problem. Copy paste Excel

Tables into your report for answering questions).

Month 1 2 3 4 5 6 7 8 9 10

Value 12 19 24 13 20 23 15 21 23 18

a) Use the Naïve Method of forecasting. What is the forecast for month 11?

b) Use the Forecasting Method that uses the average of all the data available until that

period as the forecast for the next period. What is the forecast for month 11?

c) Which method appears to provide the better forecast? Use different Measures of Forecast

Accuracy in making this determination.

2. Refer to the gasoline sales time series data in Table 18.1 of the Text Book. (Use Excel for

this problem. Copy paste Excel Tables into your report for answering questions).

a) Compute two- week, three-week, and four- week moving average forecasts for the time

series data.

b) Compute Measures of Forecast Accuracy like MAE, MSE, and MAPE.

c) Which method of forecasting of the three (two, three, or four- week moving average

models) would you prefer to use for future forecasting purposes? Justify your answer.

3. For the Hawkins Company, the monthly percentages of all shipments received on time over

the past 12 months are: 99, 104, 101, 98, 100, 104, 101, 102, 98, 100, 101, and 102.

a) Construct a time series plot. What type of pattern exists in the data?

b) Compare the three- month moving average approach and exponential smoothing

approach for α = .3. Which method provides a better forecasting model?

c) What is the forecast for next month in each case?

4. Consider the following time series.

t 1 2 3 4 5 6 7 8 9 10

Yt 120 110 100 96 94 92 88 84 82 78

a) Construct a time series plot. What type of pattern exists in the data?

b) Develop the linear trend equation. What are the values for slope and intercept?

c) What is the forecast for t = 11?

d) Is the linear trend statistically significant? Use α = .05

e) What is the Goodness of fit measure (strength of this linear trend) is?

Homework #8 *************************************************** ***************************

Instructions: Solve all the problems. All problems carry 20 points each. Maximum score for Homework #8 is 80 points. Note: Use EXCEL as appropriate. Copy the tables into your report and finish up the rest (answering questions and conducting hypothesis tests). Using Excel will save you a lot of time.

Due: Attach your report on Canvas before 1:00 p.m. Wednesday, Nov. 20th.

Additional Suggestions/Instructions:

1) No need for typing. You can do your work by hand on paper. 2) If you use an A-4 size paper to do your Homework on one side, perhaps it will be easier for

you to scan. 3) Remember to write down your name on the report and number the pages. 4) Create a single scanned file. Verify and ensure everything with your report is in order.

Word or pdf formats are acceptable. 5) Name your report file: "Your Full Name"+"Homework Number". 6) Upload your report file on Canvas and verify if everything is fine. 7) Do not wait until the last minute. The deadline is strictly enforced by Canvas. No

hardcopy submissions are accepted. No e-mail submissions are accepted. If your file is not uploaded to Canvas before the deadline, you would lose points.

8) If anyone needs help with scanning, please stop by the Information Commons Help

Desk by the second floor Rotunda and seek help. They will explain what you need to do and you will be able to scan your work. Their service is totally free of charge for you. Information Commons is open 9 a.m. – 9 p.m. Monday through Thursday; 9 a.m. – 5 p.m. on Friday; and 8 a.m. – 5 p.m. on Saturday.

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2

1. Consider the following time series data. (Use Excel for this problem. Copy paste Excel Tables into your report for answering questions).

Month 1 2 3 4 5 6 7 8 9 10

Value 12 19 24 13 20 23 15 21 23 18

a) Use the Naïve Method of forecasting. What is the forecast for month 11? b) Use the Forecasting Method that uses the average of all the data available until that

period as the forecast for the next period. What is the forecast for month 11? c) Which method appears to provide the better forecast? Use different Measures of Forecast

Accuracy in making this determination.

2. Refer to the gasoline sales time series data in Table 18.1 of the Text Book. (Use Excel for this problem. Copy paste Excel Tables into your report for answering questions).

a) Compute two- week, three-week, and four- week moving average forecasts for the time

series data. b) Compute Measures of Forecast Accuracy like MAE, MSE, and MAPE. c) Which method of forecasting of the three (two, three, or four- week moving average

models) would you prefer to use for future forecasting purposes? Justify your answer. 3. For the Hawkins Company, the monthly percentages of all shipments received on time over

the past 12 months are: 99, 104, 101, 98, 100, 104, 101, 102, 98, 100, 101, and 102.

a) Construct a time series plot. What type of pattern exists in the data? b) Compare the three- month moving average approach and exponential smoothing

approach for α = .3. Which method provides a better forecasting model? c) What is the forecast for next month in each case?

4. Consider the following time series.

t 1 2 3 4 5 6 7 8 9 10

Yt 120 110 100 96 94 92 88 84 82 78

a) Construct a time series plot. What type of pattern exists in the data? b) Develop the linear trend equation. What are the values for slope and intercept? c) What is the forecast for t = 11? d) Is the linear trend statistically significant? Use α = .05 e) What is the Goodness of fit measure (strength of this linear trend) is?