Managers and analysts routinely collect and examine key performance measures over time to better understand their operations and make forecasts of those measures in the future. Although some techniques for analyzing time series data and generating forecasts are sophisticated and require specialized expertise, there are methods that are understandable and applicable by anyone with basic algebra skills and the support of a spreadsheet package. By applying these fundamental methods themselves rather than turning over both the data and the responsibility for analysis and forecasting to an expert, managers will develop a richer understanding of their environment.

This text is intended to describe these fundamental techniques to managers, data analysts, and students. The analysis of time series data is enhanced by the use of computers. Spreadsheet software is well suited for the methods discussed in this text. Examples in the text apply Microsoft Excel. Readers will have access to the example workbooks and Adobe Flash videos illustrating key steps using Microsoft Excel from the Business Expert Press website. This text is a companion to a book that addresses sample (cross-sectional) data and statistical inference. Together these books will equip the manager and the student with a solid understanding of applied data analysis and prepare them to apply the methods themselves.