01 / Reading Guide
Reading Guide
Who this book is for
For business undergraduates, MBA students and analysts who need a repeatable forecasting process. It is a focused continuation after general business statistics, especially when observations arrive in time order. The emphasis is practical judgment and reproducible work rather than a comprehensive mathematical theory of stochastic processes.
Prerequisites
Introductory statistics and school algebra support most chapters. Learn basic R alongside the examples; selected sections need matrices.
What it covers
Exploration and decomposition lead to forecast evaluation, regression, exponential smoothing, ARIMA and grouped series. The third edition uses tsibble and fable with the tidyverse. These tools help organize the workflow, but interpreting patterns, uncertainty and errors remains the reader’s responsibility.
How to use it
Choose a series with a clear business question and plot it before fitting a model. Compare each proposed method with a simple benchmark using a held-out period or rolling evaluation. Report prediction intervals alongside point forecasts. Save the data transformation steps and software versions so that another reader can rerun the analysis.
Edition and sources
The preface identifies the 2021 third edition and explains its intended readers. This record links the freely readable, continually updated online text, whose contents can differ from the 2021 print copy. No print ISBN is assigned to the web resource. Guidance also draws on the forecasting toolbox chapter.
