Time Series Analysis - Introductory Overview

Time Series Analysis

General Introduction

In the following topics, we will first review techniques used to identify patterns in time series data (such as smoothing and curve fitting techniques and autocorrelations), then we will introduce a general class of models that can be used to represent time series data and generate predictions (autoregressive and moving average models). Finally, we will review some simple but commonly used modeling and forecasting techniques based on linear regression. For more information on these topics, click on the topic name below.

Identifying Patterns in Time Series Data