A Comprehensive Textbook on Sample Surveys

09.05.2023

Englisch

9789811914201

Springer Singapore

Indian Statistical Institute Series

Nein

Arijit Chaudhuri, Sanghamitra Pal

257

Broschiert

Arijit Chaudhuri is an honorary visiting professor at the Applied Statistics Unit at the Indian Statistical Institute (ISI), Kolkata, India, since 1st September 2005. Professor Chaudhuri holds a Ph.D. in Statistics in the area of sample surveys from the University of Calcutta, Kolkata, India, from where he also has graduated. He worked as a postdoctoral researcher for two years at the University of Sydney (1973–1975), Australia. He retired as a professor from the ISI, Kolkata, India, on 31st August 2002, where he then continued to work as a CSIR emeritus scientist for three years up to 31st August 2005. His areas of research include mean square error estimation in multi-stage sampling, analytical study of complex surveys, randomized response surveys, and small area estimation. In the year 2000, he was elected as the President of the Section of Statistics for the Indian Science Congress and worked for the Government of West Bengal for 12 years as the Committee Chairman for the improvement of crop statistics. He has also worked with the Government of India to apply sophisticated methods of small area estimation in improving state and union territory level estimates of various parameters of national importance. He has worked on various global assignments upon invitation, including visiting professorships at several universities and statistical offices in the USA, Canada, England, Germany, the Netherlands, Sweden, Israel, Cyprus, Turkey, Cuba, and South Africa, from 1979 to 2009. He has successfully mentored 10 Ph.D. students and published more than 150 research papers in peer-reviewed journals, a few of them jointly with his students and colleagues. He is the author of 11 books on survey sampling.

sample sureveys, sampling theory, field survey techniques, indirect and randomized survey techniques, adaptive and network sampling, qualitative and quantitative data, small domain statistics development, small area estimation, Bayes approach, imputation

PBT - Wahrscheinlichkeitsrechnung und Statistik

235 mm

15.5 cm