Topic:
Bayesian Statistics
Abstract:
The talk would mainly deal with an Introduction to elementary Probability Theory, Statistical Inference. It would also deal with the Frequentist versus Bayesian Paradigm, Prior, Likelihood & Posterior, Statistical Decision Theory, Bayesian Point & Interval Estiamtion, Hypothesis Testing & Prediction. Later point of the discussion will be on how to choose a Prior, Bayesian Inference for the Normal & Binomial Model, Bayesian Regression and finally Bayesian Compution - Markov Chain Monte Carlo.
Recommended Reading:
· Bayesian Statistics
http://www.mgmt.iisc.ernet.in/CM/LectureNotes/bayesian_statistics.pdf
· Markov Chain Monte Carlo
http://www.mgmt.iisc.ernet.in/CM/LectureNotes/markov_chain_monte_carlo.pdf
Bio of the Speaker:
Chiranjit Mukhopadhyay received his B.Stats (hons), M.Stat from the reputed Indian Statistical Institute, Calcutta, and PhD in Statistics from University of Missouri, Columbia, USA. He has served in the faculty of The Ohio State University, Case Western Reserve University, Bilkent University and Indian Statistical Institute, Bangalore in the past and is now an Associate Professor of Statistics in the Department of Management Studies, Indian Institute of Science. His research interests include Reliability, Statistical Quality Control, Equity Market Modeling, Market Micro-Structure etc. and has guided several Ph.D., M.Tech and MBA theses and published on these topics in main stream Statistics as well as Finance journals and conferences. Apart from these academic activities is also actively involved in industrial consulting and has provided consultancy services to HLL, Quest, L&T, Indal etc. on sales forecasting, quality engineering, reliability, geostatistical modeling etc. Chiranjit also loves to play Bridge and is also game for long drives.
Homepage: http://mgmt.iisc.ernet.in/CM/cmhomepage.html
E-mail: cm@mgmt.iisc.ernet.in
Additional Material (References, Slides & Lecture Notes):