Practical Data Analysis with JMP, Second Edition, 2nd Edition

20 Basic Forecasting Techniques

Overview

Detecting Patterns Over Time

Smoothing Methods

Simple Moving Average

Simple Exponential Smoothing

Linear Exponential Smoothing (Holt’s Method)

Winters’ Method

Trend Analysis

Autoregressive Models

Application

Overview

For much of this book, we have examined variation across individuals measured simultaneously. This chapter is devoted to variation over time, working with data tables in which columns represent a single variable measured repeatedly and rows represent regularly spaced time intervals. In many instances, time series data exhibit common, predictable patterns that we can use to make forecasts about future time periods. As we move through the chapter, we’ll learn several common techniques for summarizing ...