About this course
Takes delegates beyond the basics of R into statistical modelling and visual communication of results. Content covers multiple and generalised linear regression, panel and time series models, model diagnostics and selection, simulation, advanced ggplot2 graphics, interactive visualisation, and automated reporting with R Markdown. Delegates complete a full analysis project from raw data to finished report.
Why this course
Analysts who already use R often stop at descriptive work and simple regressions. Moving to proper modelling and automated reporting lets research and statistics units answer harder policy questions, update regular publications with little manual effort and present findings in a form decision-makers can follow.
What delegates will be able to do
By the end of the course, delegates will be able to
- Estimate and compare multiple regression and generalised linear models in R
- Fit and diagnose panel data and time series models
- Create layered and interactive visualisations to communicate findings
- Produce automated reports and briefs using R Markdown
- Complete an end-to-end analysis project from raw data to report
Who should attend
Economists, statisticians, data analysts and researchers who already use R for basic data handling. Suited to central banks, statistics offices, ministries and research institutes. Delegates should be comfortable with R scripts and the tidyverse.
How it is delivered
Project-based computer sessions in R and RStudio, combining short demonstrations with modelling exercises and an individual analysis project on a dataset of the delegate's choice. It is available as a public course, in-house at your premises, or as live virtual sessions. Duration and dates are confirmed in your quote, and in-house groups can have the examples and exercises fitted to their organisation.