Programme PGP Term IV Academic Year 2021-22

Course title Bayesian Methods for Data Analysis Area Production & Quantitative Methods Credits 1.00

Prof. Karthik Sriram

Course Description & Objectives
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 and

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.

Interactive Lectures and hands on practical exercises.