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Introduction to Bayesian Statistics

Introduction to Bayesian Statistics

₹10000

"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on M

10 months ago
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Mathematics for IIT JEE Mains and Advance

Mathematics for IIT JEE Mains and Advance

₹750

This new edition of a very well-known and popular IIT-JEE Mathematics prep book carries all its hallmark features of the earlier editions. Along with exploration of theory, deƒOnitions and derivations, the book carries a plenty of solved examples - from simple ones to more complex and tough problems in each chapter - to hand-hold students into the process of problem solving. After every important topic, problem exercises have been given which the students are expected to solve on their own. Hints and solutions of these are given in case the students need to refer to these. Apart from the newer Main and Advanced problems, this edition carries all the old classic problems of the past decades from JEE as well as other similar examinations, because many such questions and their solutions are thought to be extremely important for developing a proper pedagogical approach to solving IIT-JEE Mathematics problems irrespective of year of examination. An assortment of selected problems of Main and Advanced exams of the last 5 years have been given at the end of the book along with solutions which the students can use as integrative practice questions and also get familiar with the trends of the recently held examinations. For an audio-visual demo and to get a closer look-and-feel of solving questions live, students are advised to go through the videos given for each chapter by scanning the QR codes given on the chapter-opening page. Each of these videos have been prepared with utmost care by keeping the natural ƒPow of treatment of the concepts in the book. These are accessible free of any additional cost to the students!

10 months ago
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