Organisations of all types collect vast amounts of time series data, and there is a growing need for time series analytics to understand how things change in our fast-moving world. This tutorial provides a practical introduction to time series analytics and forecasting using R, utilising the tidyverse and tidy time series tools to enable analysis across many time series. Attendees will learn about commonly seen time series patterns, and how to find them with specialised time series graphics created with ggplot2. Then we will use fable to capture these patterns with statistical time series models, and produce probabilistic forecasts. Finally, participants will gain insights into evaluating model performance, ensuring the accuracy and reliability of their forecasts. Through a combination of foundational concepts and practical demonstrations, this tutorial equips participants with the skills to extract meaningful insights from time series data for informed decision-making in various domains.

Learning Outcomes:

• How to use the tidyverse to wrangle and manipulate time series data.
• Visualise data and identify common time series patterns.
• Produce forecasts from a statistical model that captures dynamic time series patterns.
• Evaluate the model’s forecasting performance to select the best model.