This web
site contains notes for an advanced elective course on statistical forecasting
that has been taught at the Fuqua School of Business, Duke University, for many
years. Most of the examples of computer output were generated with Statgraphics, a general-purpose statistical
analysis program that offers interactive graphics and has especially good
features for fitting and comparing models for time series data, including a
forecasting procedure that I designed. The site is currently undergoing some
long-overdue upgrades. Future material dealing with multivariate data analysis
and regression models will include examples of output generated by RegressIt, a free* *Excel add-in that I have developed more recently, whose procedures
for descriptive data analysis and ordinary linear regression offer high-quality
output and support for good modeling practices. However, these notes are
platform-independent. Any statistical software package ought to provide the
analytical capabilities needed for the various topics covered here.

Principles and risks
of forecasting (pdf)

Famous forecasting quotes

How to move data around

Get to know your data

Inflation adjustment (deflation)

Seasonal adjustment

Stationarity and differencing

The logarithm transformation

Statistics
review and the simplest forecasting model: the sample mean (pdf)

Notes on the random
walk model (pdf)

Mean (constant) model

Linear trend model

Random walk model

Geometric random walk model

Three types of forecasts: estimation period, validation
period, and the future

Notes on
forecasting with moving averages (pdf)

Averaging and exponential smoothing models

Spreadsheet implementation of seasonal adjustment and
exponential smoothing

Notes on linear
regression analysis (pdf)

Introduction to linear regression analysis

Regression example, part 1:
descriptive analysis

Regression example, part 2: fitting a simple model

Regression example, part 3: transformations of variables

What to look for in regression output

What's a good value for R-squared?

What's the bottom line? How to compare models

Testing the assumptions of linear regression

Additional notes on regression analysis

Spreadsheet with
regression formulas

Stepwise and all-possible-regressions

Notes on nonseasonal
ARIMA models (pdf)

Slides on seasonal and
nonseasonal ARIMA models (pdf)

Introduction to ARIMA: nonseasonal models

Identifying the order of differencing

Identifying the orders of AR or MA terms

Estimation of ARIMA models

Seasonal differencing

Seasonal random walk: ARIMA(0,0,0)x(0,1,0)

Seasonal random trend: ARIMA(0,1,0)x(0,1,0)

General seasonal ARIMA models: ARIMA(0,1,1)x(0,1,1) etc.

Summary of rules for identifying ARIMA models

ARIMA models with regressors

Steps in choosing a forecasting model

Forecasting flow chart

Data transformations and forecasting models: what to use
and when

Automatic forecasting software

Political and ethical issues in forecasting

How to avoid trouble

Forecasting Principles web site
(J. Scott Armstrong and Kesten Green)

Forecasting Principles and Practice
on-line textbook (Rob Hyndman and George Athanasopoulos)

International
Institute of Forecasters links (sites, references, software)

StatPages web site (John Pezzullo)

StatSci web site (Gordon Smyth)

Talk Stats forum

StackExchange Cross-Validated forum

(c) 2014, All Rights Reserved

This site receives around 2000 visitors per day on average. Last
updated on September 20, 2014.