Introduction to Bayesian Statistics - Virtual Classroom

Date: Tuesday 13 July 2027 9.30AM - Wednesday 14 July 2027 5.00PM
Location: Online
CPD: 12.0 hours
RSS Training


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Level: Intermediate (I)

The course takes place on two consecutive days on the 13th and 14th of July. The times of the session on each day are 09:30am - 5:00pm.

This course aims to provide a working knowledge of Bayesian statistics for interested researchers.
 
Bayesian statistics has become a standard approach for many applied statisticians across a wide variety of fields due to its conceptual unity, clarity and practical benefits. However, because training in Bayesian methods is often not a standard part of research curricula, the benefits of Bayesian statistics have been slower to reach applied researchers.
 
Level: Intermediate (I)

The course takes place on two consecutive days on the 13th and 14th of July. The times of the session on each day are 09:30am - 5:00pm.
Bayesian statistics has become a standard approach for many applied statisticians across a wide variety of fields due to its conceptual unity, clarity and practical benefits. However, because training in Bayesian methods is often not a standard part of research curricula, the benefits of Bayesian statistics have been slower to reach applied researchers.


Learning Outcomes

  • Understand the main differences and similarities between Bayesian and classical analysis
  • Understand basic concepts in Bayesian analysis, such as priors and posteriors
  • Formulate basic priors using knowledge from their area of expertise
  • Interpret the results of a Bayesian analysis
  • Use R and JAGS to perform a Bayesian analysis
  • Diagnose basic problems that can arise in Bayesian analysis


Topics Covered

  • Basic inference
  • Bayesian statistics
  • Markov Chain Monte Carlo
  • Multilevel models 


Target Audience

The target audience for this short course is researchers with a working knowledge of classical statistics who are curious about Bayesian statistics and how it can improve their statistical practice, and who want enough practical knowledge to start using Bayesian statistics. 


Knowledge Assumed

Basic knowledge of probability and common statistical techniques (t-tests, linear models, etc.). Basic working knowledge of R.

 

Richard Morey

Richard D. Morey is a senior lecturer in the School of Psychology at Cardiff University where he specialises in research in the theory and practice of statistical methodology. He obtained his PhD in cognition and neuroscience and a Masters degree in statistics from the University of Missouri.

 

Fees

   

Registration before 
13 April 2027

 

Registration on/after
13 April 2027

                                  


Non Member 

RSS Fellow 

RSS CStat/Gradstat/Data Analyst 
also MIS & FIS

 

£835.00 +VAT 

£710.00 +VAT

£665.00 +VAT

£875.00 +VAT

£745.00 +VAT

£695.00 +VAT

Group discounts are also available*:


3-5 people

6-8 people

9+ people
*Discount only applies to non-member price

 


10% discount

15% discount

20% discount