Programme

PGP

Term

IV

Academic Year

2021-22

Course title

Bayesian Methods for Data Analysis

Area

Production & Quantitative Methods

Credits

1.00

Instructor(s)

Prof. Karthik Sriram

Course Description & Objectives

Introduction: In many decision making situations, data may be limited, or even if available may be inadequate if not combined with expert judgement based on contextual knowledge. In such situations, a systematic approach to incorporating expert opinions or prior information about the context along with the data becomes important. This course introduces basic principles and methods in Bayesian data analysis that are relevant for many management problems requiring data analytics. The ideas will be introduced by using a number of practical examples motivated from real life applications. In-class learning will happen through several hands-on practical exercises. Although the focus will be on practical application of concepts, adequate theoretical ideas will be discussed to help meaningfully formulate and solve problems. Practical exercises will be mostly done in R and Excel. The required R coding will be covered during the course. R software and the supporting GUI, can be freely downloaded from https://cran.r-project.org/ and https://www.rstudio.com Objectives:  To provide a good understanding and working knowledge of basic principles and methods in Bayesian data analysis, so that the participant can formulate solutions to management problems where expert judgement based on contextual knowledge and data driven models need to be systematically combined.

Pedagogy

Interactive Lectures and hands on practical exercises.