Time Series Analysis and Forecasting
This module covers the use of STATGRAPHICS in analyzing time series data.

Module length: 0.5 day

Outline:

Descriptive Methods

Time Sequence Plots
Subseries Plots
Autocorrelations and Partial Autocorrelations
Periodograms
Tests for Randomness
Cross-correlation Functions

Smoothing

Weighted Moving Averages
Nonlinear Resistant Smoothers
Combining More than One Smoother

Seasonal Decomposition

Time Series Models
Estimating the Components
Generating Seasonally Adjusted Data

Forecasting

Moving Averages
Trend Models
Exponential Smoothing
ARIMA Models
Selecting a Forecasting Model
Automatic Model Selection