Level: Intermediate (I)
This two-day virtual 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.
Please note: Bookings will close 4 working days before the course start date or when the course has reached its maximum capacity.
/RSS-Quality-Mark-reduced-3.jpg.aspx "RSS-Quality-Mark-reduced-3.jpg")
This course has the Society's Quality Mark so can be used as part of your application for professional membership including Data Analyst.
Level: Intermediate (I)
This two-day virtual 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.
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
15 February 2023
|
Registration on/after
15 February 2023
|
|
|
Non Member
RSS Fellow
RSS CStat/Gradstat/Data Analyst
also MIS & FIS
|
|
£654.38+vat
£556.92+vat
£524.79+vat
|
£728.28+vat
£617.97+vat
£581.55+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
|
|