Probability and Statistical Inference Statistics: A Series of Textbooks and Monographs Series
Auteur : Mukhopadhyay Nitis
Priced very competitively compared with other textbooks at this level!
This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts.
Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, Probability and Statistical Inference
Employing over 1400 equations to reinforce its subject matter, Probability and Statistical Inference is a groundbreaking text for first-year graduate and upper-level undergraduate courses in probability and statistical inference who have completed a calculus prerequisite, as well as a supplemental text for classes in Advanced Statistical Inference or Decision Theory.
Nitis Mukhopadhyay
Date de parution : 09-2020
15.2x22.9 cm
Date de parution : 03-2000
Ouvrage de 696 p.
15.2x22.9 cm
Thème de Probability and Statistical Inference :
Mots-clés :
MP Test; Minimal Sufficient Statistic; Probability rigorous theory; Fixed Width Confidence Interval; Central limit theorem; Iid Random Variables; Statistical inference; Bivariate Normal; Probability theory; Simple Null Hypothesis; Cornish-Fisher expansions; Behrens Fisher Problem; Confidence Interval; Posterior PDF; Confidence Coefficient; HPD Credible Interval; Null Hypothesis; Posterior Pdf; Bounded Risk Point Estimation; Optimal Fixed Sample Size; LR Test; Posterior Distribution; Ump Test; MLR Property; Confidence Interval Estimator; Approximate Pivot; Implementable Form; Fixed Width Confidence Interval Procedure; National Academy; Pilot Sample Size