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Statistical Forecasting

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Author:Robert Nau
Description: Lecture notes and teaching materials for a course on statistical forecasting, with particular focus on regression and time series models. Output from Statgraphics and RegressIt illustrate sections such as "Get to know your data" (famous forecasting quotes, inflation adjustment, seasonal adjustment, stationarity and differencing, and more); "Introduction to forecasting" (linear trend model, random walk model, geometric random walk model, etc.); "Averaging and smoothing models" (spreadsheet implementation of seasonal adjustment and exponential smoothing, etc.); "Linear regression models" (baseball batting averages, beer sales vs. price, what's a good value for R-squared? and more); "ARIMA models for time series forecasting" (nonseasonal models, identifying the order of differencing, seasonal random walk, ARIMA models with regressors, etc.); and "Choosing the right forecasting model" (forecasting flow chart, political and ethical issues in forecasting, etc.).

Levels: College
Languages: English
Resource Types: Course Notes, Reference Sources
Math Topics: Data Analysis, Statistics

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