This chapter presents a number time-series methods: naive, smoothing, decomposition, regression, and percent sales forecasting.  Fully worked out examples of each are provided.
 
Introduction
Case Study: Apple
Naïve Methods: Last-Year Constant
Naïve Methods: Last-Year Rate of Change
Smoothing Method: Moving Averages
Smoothing Method: Moving Average with Weighting of Observations
Smoothing Method: Exponential Smoothing
Seasonality Method: Forecasting Seasonality in Time Series Data
Regression Methods: Dummy Variable Regression for Seasonal Data
Regression and Prediction Intervals
Projection Method: Percent of Sales
Summary
Appendix 1: Apple Inc. Annual Revenue in $ Billions, 1977–2020
Appendix 2: Apple Inc. Quarterly Annual Revenue in $ Billions, 2012–2020
Appendix 3: Time Series Decomposition Data
Section VI: Prescriptive Analytics Overview