Standard syllabus
Forecasting · Undergraduate · Math
Learning objectives from the Forecasting syllabus, grouped by unit. Click an objective for study materials.
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Forecasting — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
Forecasting foundations
- Components of time series: trend, seasonality, cycle — Components of time series: trend, seasonality, cycle
- Naive and average forecasting — Naive and average forecasting
- Seasonal naive benchmarks — Seasonal naive benchmarks
- Moving averages — Moving averages
- Exponential smoothing — Exponential smoothing
- Forecast accuracy metrics: MAPE, MAD, RMSE — Forecast accuracy metrics: MAPE, MAD, RMSE
- Holdout samples — Holdout samples
- Rolling forecasts — Rolling forecasts
Regression-based forecasting
- Trend models — Trend models
- Polynomial regression — Polynomial regression
- Seasonal dummy variables — Seasonal dummy variables
- Autoregressive forecasting models (intro) — Autoregressive forecasting models (intro)
- Leading indicators — Leading indicators
- Causal forecasting — Causal forecasting
- Combining forecasts — Combining forecasts
Judgment and communication
- Role of judgmental adjustments — Role of judgmental adjustments
- Forecast intervals — Forecast intervals
- Scenario analysis — Scenario analysis
- Forecasting for inventory — Forecasting for inventory
- Demand planning — Demand planning
- Presenting forecasts to decision makers — Presenting forecasts to decision makers
Learning objectives
Click an objective for study materials.
Forecasting foundations
- Components of time series: trend, seasonality, cycle — Components of time series: trend, seasonality, cycle
- Naive and average forecasting — Naive and average forecasting
- Seasonal naive benchmarks — Seasonal naive benchmarks
- Moving averages — Moving averages
- Exponential smoothing — Exponential smoothing
- Forecast accuracy metrics: MAPE, MAD, RMSE — Forecast accuracy metrics: MAPE, MAD, RMSE
- Holdout samples — Holdout samples
- Rolling forecasts — Rolling forecasts
Regression-based forecasting
- Trend models — Trend models
- Polynomial regression — Polynomial regression
- Seasonal dummy variables — Seasonal dummy variables
- Autoregressive forecasting models (intro) — Autoregressive forecasting models (intro)
- Leading indicators — Leading indicators
- Causal forecasting — Causal forecasting
- Combining forecasts — Combining forecasts
Judgment and communication
- Role of judgmental adjustments — Role of judgmental adjustments
- Forecast intervals — Forecast intervals
- Scenario analysis — Scenario analysis
- Forecasting for inventory — Forecasting for inventory
- Demand planning — Demand planning
- Presenting forecasts to decision makers — Presenting forecasts to decision makers
Multi-Unit Problems
Course-level sets that combine skills across study units (coming soon).
Browse Multi-Unit ProblemsWhat each unit includes
Open a unit below for full materials. Typical resources:
- Study guide
- Exam Strategy
- Common Mistakes
- Worksheets
- Word problems
- Mixed Practice
- Multi-Unit Problems
- Review
- Practice test
- Answer key
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Forecasting foundations
Components of time series: trend, seasonality, cycle
Coming soon - Regression-based forecasting
Trend models
Coming soon - Judgment and communication
Role of judgmental adjustments
Coming soon
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$1,162 · Forecasting · 18 tutoring hrs
Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle.