By: W Jorge Sitkewich, Mathematics and Statistics Adjunct Instructor San Jose City College. firstname.lastname@example.org. Teaching Seasonal Forecasting to Students of Statistics. Agenda. Why is forecasting important? Use a project to teach Time Series Seasonal Forecasting.
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Mathematics and Statistics Adjunct Instructor
San Jose City College. email@example.com
Teaching Seasonal Forecasting to Students of Statistics
Table 7b. “U.S. Regional Electricity Retail Sales”
Phase 1. Select the specific project and justify it as a valid team activity for this course.
Phase 2. Estimate the Schedule and adjust the Project Scope for a duration of four calendar weeks.
Phase 3. Execute the Method using available Technology. Generate spread sheets and Charts.
Phase 4. Estimate errors of the Model and provide Conclusions and References.
Phase 5. Create PowerPoint Summary Presentation. Each team presents their summary as a 10 minute presentation to conclude the Project.
Refer to the Rubric provided in Part A handout #1
Refer to Part B, Handout #1
Refer to Part C, Handout #1
Refer to Part A, Handout #2
Refer to Part B, Handout #2
Refer to Part A, Handout #3
Refer to Part B, Handout #3
Even though the more advanced methods may provide smaller forecasting error, they are harder to visualize and to perform with simple laptop tools.
EIA data set downloaded July 17, 2009: http://tonto.eia.doe.gov/cfapps/STEO_Query/steotables.cfm?tableNumber=8
Mason,R., Lind,D. Statistical Techniques in Business and Economics. R.D.Irwin 1993
X-12, ARIMA Reference manual, (July 17, 2009), http://www.census.gov/srd/www/x12a/x12down_pc.html
Ellis,Wade. Inquiry-base Software MicroWorlds: Promoting Understanding and Retention of Concepts. International Merlot Conference 2009
Refer to Part C, Handout #3
Quote from Ellis Wade’s paper:
“…research indicates that students retain a concept only if the concept is learned to the level of problem-solving (level 4) or at least application of the concept (level 3 of the Bloom taxonomy). “