Applied Bayesian Data Analysis for Social Science

Date:

01/04/2025

Organised by:

London School of Economics

Presenter:

Dr Patrick English

Level:

Advanced (specialised prior knowledge)

Contact:

Crystal Chia
methodology.research@lse.ac.uk

Map:

View in Google Maps  (WC2B 4DS)

Venue:

CON 1.01, Connaught House, LSE
65 Aldwych London

Description:

In this workshop you will learn the theory behind Bayesian inference, its critiques of frequentist statistics, and the application of Bayesian regression models in the R statistical language. We will begin the course by outlining frequentist logic and the Bayesian critique of its assumptions and applications and then move to introduce the concepts of Bayesian inference and estimating probability in a Bayesian framework. The practical work will then involve using the R statistical language to estimate, interpret, and visualise Bayesian regression models and their outputs. While the course will involve theoretical topics and have statistical components, it will be aimed at social scientists and the kinds of applications and interactions that they as researchers will have with Bayesian data analysis.

Preparation
Please bring your own laptop, and on top of that -

  1. install the recent versions of both R and R Studio;

  2. install the rstanarm, broom.mixed, and bayesplot packages within R; and

  3. test the R script (you will receive it before the workshop). If it works and runs, you are ready for the lecture.


Session Details
Time: 10:00 - 15:00 (12:00 - 13:00 Lunch break)
Date: 1 April 2025
Mode: In person only at CON 1.01

Cost:

Free

Website and registration:

Register for this course

Region:

Greater London

Keywords:

Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, ICT and Software, Research Management and Impact, Research Skills, Communication and Dissemination


Related publications and presentations from our eprints archive:

Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
ICT and Software
Research Management and Impact
Research Skills, Communication and Dissemination

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