Time series data is everywhere, from crime statistics to web traffic, and knowing how to work with them means being able to spot trends, understand seasonality, and forecast what happens next. Time series analysis and forecasting are among the most widely used quantitative techniques in both business and research, and these skills are increasingly in demand as more of our data arrives stamped with a date and time.
Format
This free online workshop will run in two linked parts with a break in between. Part 1 is a concepts talk and Part 2 is a dedicated hands-on code demo. Attendees are welcome to join either or both.
The session will include:
- An introduction to time series data, and how it differs from cross-sectional and pooled data.
- The core components of time series analysis: trend, seasonality, cyclic patterns and noise.
- Decomposition and how to check a series for stationarity.
- An introduction to ARIMA/SARIMA forecasting models.
- A live coding demonstration in R, using publicly available, police-recorded crime data.
- A Q&A session.
Participants will have access to all workshop materials, including slide decks and code, via a GitHub repository, circulated ahead of the session alongside a short glossary of key terms so you can arrive already comfortable with the vocabulary.
Prerequisites
No formal prerequisites are required to attend. However, those who wish to actively participate in the coding demonstration should have access to R (and RStudio) and a basic working knowledge of R, e.g. setting a working directory, reading data in, saving manipulated data under new names, and running basic descriptive statistics.
Level
Beginner to Intermediate
Target Audience
Researchers, analysts, and anyone interested in learning how to forecast time series data
Presenter
Nadia Kennar, UK Data Service. Nadia is a Research Associate at the UK Data Service within the Computational Social Science Team (CSS). She has a MRes in Criminology and Social Statistics. Nadia enjoys developing engaging webinars and workshops that incorporate live coding and has a particular interest in demonstrating and discussing coding techniques. She is motivated by seeing participants apply these concepts to advance their own research and professional work.