22
Oct
A case for Bayesian 4: audience-led readings
Each session in this series will consider a different reading presenting a case for Bayesian. We invite participants to nominate and vote on articles to be read and presented in each session. Participants may suggest their own article or choose from the list provided.
15
Oct
The Meaning of Logistic Regression: Probing Predictions
Logistic regression provides a great introduction to generalized linear models (GLMs); it is in fact a GLM with a binomial sampling model, so is sometimes referred to as binomial regression. We will explore both traditional (Frequentist) as well as Bayesian approaches to modelling how a binary response (also referred to as a dependent variable or an outcome) may relate to several explanatory variables (also known as independent variables or predictors).
08
Oct
A case for Bayesian 3: audience-led readings
Each session in this series will consider a different reading presenting a case for Bayesian. We invite participants to nominate and vote on articles to be read and presented in each session. Participants may suggest their own article or choose from the list provided.
01
Oct
The Meaning of Logistic Regression: Explainable Modelling
These 'Stat-a-along' sessions are designed so that you can replay the session slowly, whilst following similar steps with your own data.
24
Sep
A case for Bayesian 2: audience-led readings
Each session in this series will consider a different reading presenting a case for Bayesian. We invite participants to nominate and vote on articles to be read and presented in each session. Participants may suggest their own article or choose from the list provided.
17
Sep