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Questions and Answers
What is the primary goal of the assignment?
Seasonal indexes can be found by removing the irregular component from the time series.
True
What method is used to capture the trend and seasonal patterns for forecasting in this assignment?
Ratio-to-Moving Average method
The assignment requires the submission of files in ______ format.
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Match the months with their corresponding ice cream consumption in 2021 (in million tons):
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What is the RMSE used for in this assignment?
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Visual plots are not required for this assignment.
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What are centered moving averages (CMA) used for in time series analysis?
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Study Notes
Assignment Overview
- Total points available: 100
- Submission format: Word or Excel files through D2L
- Work must be shown clearly and comprehensively
- Grading criteria:
- Accuracy and completeness of calculations
- Accuracy of relevant graphs
- Clarity and completeness of explanations, interpretations, and conclusions
Ice Cream Consumption Data
- Data provided for four years (2018-2021)
- Monthly consumption data in million tons
- Table includes monthly consumption figures from January to December
Analysis Steps
- Plot the time series: Visualize the ice cream consumption to identify trends and seasonal patterns
- Seasonality and trends: Comment on any visible seasonality and overall trend from the plot
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Centered Moving Averages (CMA):
- Estimate CMA for the monthly consumption series
- Plot CMA and provide commentary on the results
Seasonal and Irregular Components
- Estimate S, I components: Focus on seasonal and irregular movements in the data
- Seasonal indexes: Calculate seasonal indices for all 12 months after removing irregular components
- De-seasonalized levels: Derive de-seasonalized values for the consumption series
- Plot & comment: Visual representation of de-seasonalized data with commentary
Linear Regression for Trend Estimation
- Trend values: Calculate trend values for sample years and for each month in 2022 using linear regression
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Forecasting:
- Utilize the Ratio-to-Moving Average method for 2022 forecasts
- Incorporate trend and seasonal patterns in forecasts
- Plot forecasted values: Display forecasted consumption for 60 periods, including all 12 months of 2022
Error Analysis
- In-sample error measurement: Plot the errors associated with the in-sample periods
- RMSE calculation: Compute Root Mean Square Error to evaluate forecast accuracy
- Error plot commentary: Analyze the error plot for visible patterns or the lack thereof
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Description
This assignment requires you to solve problems using Excel, demonstrating complete calculations, relevant graphs, and necessary explanations. To achieve full points, ensure that your work is accurate and your explanations are thorough. Submit your work in Word or Excel format via D2L.
