Statistical inference

By:

Casella, George

Contributor(s):

Berger, Roger L

Material type: Text

TextPublication details: New Delhi Cengage 2002Edition: 2nd edDescription: 660pISBN:

9788131503942

Subject(s):

DDC classification:

519.5 CAS

Summary: This book builds theoretical statistics from thefirst principles of probability theory. Startingfrom the basics of probability, the authorsdevelop the theory of statistical inferenceusing techniques, definitions, and conceptsthat are statistical and are natural extensionsand consequences of previous concepts.Intended for first-year graduate students, thisbook can be used for students majoring instatistics who have a solid mathematicsbackground. It can also be used in a way thatstresses the more practical uses of statisticaltheory, being more concerned withunderstanding basic statistical concepts andderiving reasonable statistical procedures for avariety of situations, and less concerned withformal optimality investigations.FEATURES Offers new coverage of randomnumber generation, simulation methods,bootstrapping, EM algorithm, p-values, androbustness.Includes new sections on "Logistic Regression"and "Robust Regression"Restructures material for clarity purposesContains updated and expanded Exercises Key Features

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Mathematics	519.5 CAS (Browse shelf(Opens below))	Available		000957

https://www.cengage.co.in/book-list/print/statistical-inference-72

This book builds theoretical statistics from thefirst principles of probability theory. Startingfrom the basics of probability, the authorsdevelop the theory of statistical inferenceusing techniques, definitions, and conceptsthat are statistical and are natural extensionsand consequences of previous concepts.Intended for first-year graduate students, thisbook can be used for students majoring instatistics who have a solid mathematicsbackground. It can also be used in a way thatstresses the more practical uses of statisticaltheory, being more concerned withunderstanding basic statistical concepts andderiving reasonable statistical procedures for avariety of situations, and less concerned withformal optimality investigations.FEATURES Offers new coverage of randomnumber generation, simulation methods,bootstrapping, EM algorithm, p-values, androbustness.Includes new sections on "Logistic Regression"and "Robust Regression"Restructures material for clarity purposesContains updated and expanded Exercises Key Features

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