Week 2 Business Forecasting

Week 2 of Business Forecasting focuses on understanding and describing time series data through the use of key features and statistical summaries. Students learn how to transform raw data into meaningful insights by computing measures such as averages, variability, autocorrelations, and decomposition-based indicators like trend and seasonality. Emphasis is placed on interpreting these features to identify patterns, detect changes, and assess the predictability of data over time. By using analytical tools such as the feasts package, students develop the ability to evaluate whether a dataset is stable, seasonal, or random, and to determine appropriate preprocessing steps for forecasting. This foundational knowledge equips learners with the skills needed to move from simple data observation to evidence-based forecasting decisions in real-world business contexts.