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Mathematical Statistics: A Unified Introduction: Springer Texts in Statistics

Autor George R. Terrell
en Limba Engleză Hardback – 4 iun 1999
Whyanothertextbook? The statistical community generally agrees that at the upper undergraduate level, or the beginning master’s level, students of statistics should begin to study the mathematical methods of the ?eld. We assume that by thentheywillhavestudiedtheusualtwo yearcollegesequence,includingcalculus through multiple integrals and the basics of matrix algebra. Therefore, they are ready to learn the foundations of their subject, in much more depth than is usual in an applied, “cookbook,” introduction to statistical methodology. There are a number of well written, widely used textbooks for such a course. These seem to re?ect a consensus for what needs to be taught and how it should be taught. So, why do we need yet another book for this spot in the curriculum? I learned mathematical statistics with the help of the standard texts. Since then, Ihavetaughtthiscourseandsimilaronesmanytimes,atseveraldifferentuniversi ties,usingwell thought oftextbooks.Butfromthebeginning,Ifeltthatsomething was wrong. It took me several years to articulate the problem, and many more to assemble my solution into the book you have in your hand. You see, I spend the rest of my day in statistical consulting and statistical re search. I should have been preparing my mathematical statistics students to join me in this exciting work. But from seeing what the better graduating seniors and beginning graduate students usually knew, I concluded that the standard curricu lumwasnotteachingthemtobesophisticatedcitizensofthestatisticalcommunity.
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Specificații

ISBN-13: 9780387986210
ISBN-10: 0387986219
Pagini: 454
Ilustrații: XVIII, 454 p.
Dimensiuni: 155 x 235 x 28 mm
Greutate: 0.79 kg
Ediția:1999
Editura: Springer
Colecția Springer
Seria Springer Texts in Statistics

Locul publicării:New York, NY, United States

Public țintă

Lower undergraduate

Cuprins

Getting Started.- Structural Models for Data.- Least Squares Methods.- Combinatorial Probability.- Other Probability Models.- Discrete Random Variables I: The Hypergeometric Process.- Discrete Random Variables II: The Bernoulli Process.- Random Vectors and Random Samples.- Maximum Likelihood Estimates for Discrete Models.- Continuous Random Variables I: The Gamma and Beta Families.- Continuous Random Variables II: Expectations and the Normal Family.- Continuous Random Vectors.- Sampling Statistics for the Linear Model.- Representing Distributions.

Recenzii

"The book is very easy and enjoyable to read ... it offers a refreshing point of view in an area which has been dominated by texts following almost exclusively by theoretical expositions."
Short Book Reviews, Vol. 20/2, August 2000

Caracteristici

Wide audience, it will serve as an important reference for anyone in statistics and the applied disciplines * The book aims to be mathematically complete: every formula is derived, and every theorem proved at the appropriate level * Each new concept is introduced and exemplified by interesting statistical problems; and more abstract concepts appear only gradually * Emphasizes modeling of experimental data while avoiding abstract probability and distribution theory * Users are led to do mathematical statistics, not just to appreciate it, with the assistance of 500 interesting exercises