Applying linear regression to temporal data to capture structural relationships.

Predicting the future isn’t about crystal balls—it’s about data. Whether you're projecting next quarter's sales, managing a supply chain, or forecasting energy demand, time series analysis is the engine behind informed decision-making. Galit Shmueli’s guide stands out by bridging the gap between complex statistical theory and actionable business value.

Unlike many academic textbooks, this guide focuses on rather than just statistical significance. It starts with a fundamental question: How can this forecast help achieve a specific business goal? . 2. Key Forecasting Methods Covered

The book walks readers through a hierarchy of models, starting from simple baselines to advanced machine learning: