Education

Takeaways from the first UKCOTS

My favourite parts of the first ever UKCOTS (UK Conference of Teaching Statistics). Includes things I learned and things I plan to use in my own teaching statistics journey.

Statistical thinking

A 2-day course introducing the concept of statistical thinking, thinking critically in a data-driven world. Statistical thinking is a necessary skill, not just in work but in our personal lives too, allowing us to sift through conflicting claims to make decisions based on evidence.

Bayesian statistics with R

A 3-day introduction to thinking and behaving like a Bayesian! Understand the concepts behind Bayesian statistics, carry out statistical analysis using Bayesian approaches in R, and learn to interpret results from a Bayesian perspective

Regression with R

A 2-day introduction to one of the most widely used and powerful tools in quantitative analysis…regression! A comprehensive introduction to generalised linear models with applications in R.

Generalised additive models with R

A 3-day course to take your modelling to the next level. Go beyond generalised linear models with their smoother, more flexible cousins, generalised additive models!

Inferential statistics

A free, self-paced micro-course introducing the two most common inferential statistics, p-values and confidence intervals

Introduction to Statistics

A self-paced online introduction to all things statistics! Go from zero to regression via visualisation, summary statistics, and hypothesis testing.

Data visualisation with ggplot2

A one-day course introducing the powerful, flexible data visualisation package, ggplot2. Create compelling visualisations that can be used to explore data, generate hypotheses, and communicate results.

Spatial data analysis with R

A 3-day comprehensive introduction to spatial data, visualisation, and analysis. Unlock the full potential of your analysis and gain a more nuanced, geographically informed understanding of your data.

Introduction to R with Tidyverse

A 2-day introduction to the wonders of R and Tidyverse. Learn to load, manipulate, explore, and visualise data in R, and create high quality reports using RMarkdown.