ISBN-13: 9781574446135 / Angielski / Twarda / 2006 / 304 str.
Review "Professor Mukhopadhyay has done an excellent job of collecting a broad statistical knowledge base on the various topics covered and presented them in a straightforward manner Not many books on statistical inference with such features are available currently." -- Sunil K. Dhar, New Jersey Institute of Technology " This book is designed for a one-semester course in Mathematical Statistics. In many universities, graduate students from Economics, Actuarial Sciences, Finance, and several other departments do no t have enough time to take a two-semester sequenceFor them, this book is ideal. They can learn wide varieties of topics in Mathematical Statistics in one course." -- Dipak K. Dey, University of Connecticut Book Description Introductory Statistical Inference develops the concepts and intricacies of statistical inference. With a review of probability concepts, this book discusses topics such as sufficiency, ancillarity, point estimation, minimum variance estimation, confidence intervals, multiple comparisons, and large-sample inference. It introduces techniques of two-stage sampling, fitting a straight line to data, tests of hypotheses, nonparametric methods, and the bootstrap method. It also features worked examples of statistical principles as well as exercises with hints. This text is suited for courses in probability and statistical inference at the upper-level undergraduate and graduate levels.