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Consider the following time series data

06/01/2021 Client: saad24vbs Deadline: 2 Day

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) 

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