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Breakthroughs in Statistics: Volume 2: Methodology and Distribution (Springer Series in Statistics / Perspectives in Statistics)

Breakthroughs in Statistics: Volume 2: Methodology and Distribution (Springer Series in Statistics / Perspectives in Statistics)

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Creators: Samuel Kotz, Norman L. Johnson
Publisher: Springer
Category: Book

List Price: $69.95
Buy Used: $34.00
You Save: $35.95 (51%)



New (13) Used (12) from $34.00


Media: Paperback
Edition: Corrected
Number Of Items: 1
Pages: 628
Shipping Weight (lbs): 2
Dimensions (in): 5.8 x 1.5 x 1.5

ISBN: 0387940391
Dewey Decimal Number: 519.5
EAN: 9780387940397
ASIN: 0387940391

Publication Date: June 11, 1993
Availability: Usually ships in 1-2 business days

Similar Items:

  • Breakthroughs in Statistics: Volume 1: Foundations and Basic Theory (Springer Series in Statistics / Perspectives in Statistics)
  • Breakthroughs in Statistics: Volume III (Springer Series in Statistics / Perspectives in Statistics)
  • The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century
  • Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart
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Editorial Reviews:

Product Description
This is the second of a two volume collection of seminal papers in the statistical sciences written during the past 100 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Readers will enjoy a fresh outlook on now well-established features of statistical techniques and philosophy by becoming acquainted with the ways they have been developed. It is hoped that some readers will be stimulated to study some of the references provided in the Introduction (and also in the papers themselves) and so attain a deeper background knowledge of the basis of their work.


Customer Reviews:

5 out of 5 stars volume covering breakthroughs in methodology and distribution theory   February 25, 2008
 22 out of 22 found this review helpful

This volume is as praiseworthy as volume 1. However it covers a number of papers from the late 19th century and most of the twentieth century that dealt with distribution theory and statistical methodology rather than the foundational issues. Like volume 1 it was published in 1992 and includes an introduction by an expert that puts the article in contexts and explains why it is a breakthrough. All the articles are worthy of be designated as breakthrough seminal papers on the topic they cover. I will concentrate on my favorites to give the reader a flavor for the content. As with volume 1 I recommend this to any statistician or researcher interested in a deeper understanding of the history and key developments of statistics, a field developed primarily in the 20th Century.br /br /The first paper in this collection is an article by Karl Pearson where his famous chi-square statistic is first introduced. Pearson's chi square was used by him as a way to evaluate the goodness of fit of a probability model to data. The chi square distribution that is the asymptotic distribution for Pearson's test statistic is one of the most important distributions in statistics. It is used in a variety of applications in biostatistics especially where contingency tables are involved and relationships between categorical or binary variables need to be tested.br /br /The next paper is Gosset's (pen name Student) famous paper "The Probable Error of the Mean" published in 1908. This was the paper that guessed the central t distribution to be the exact sampling distribution of the t statistic used to estimate the mean of a distribution. Prior to Gosset's paper the standard normal distribution which is asymptotically correct for normally distributed samples was used. But Gosset dealt with small samples (perhaps in the range of 5 to 20) where the normal approximation is not good. Later R. A. Fisher mathematically proved the t distribution with n-1 degrees of freedom is the exact distribution for the t statistic from a sample of n independent identically distributed observations under the null hypothesis confirming Gosset's result.br /br /Other papers among my favorites are Kolmogorov's 1933 paper on the empirical distribution function and the statistic that became known as the Kolmogorov-Smirnov statistic for goodness of fit testing based on the empirical distribution, the Kaplan and Meier paper of 1958 establishing a nonparametric estimator of the survival function based on right censored time to event data, D. R. Cox's 1972 paper on the proportional hazards model for survival functions, Box and Jenkins 1962 paper on adaptive optimization and stochastic control that spawned their book on time series monitoring and feedback control systems, Nelder and Wedderburn's paper in 1972 on generalized linear models that led to the software product GLIM and later to the application in another breakthrough paper (in volume III) by Liang and Zeger to longitudinal data, and last but certainly not least Efron's 1979 Annals of Statistics paper on the bootstrap and its relationship to the jackknife which spawned a multitude of applications utilizing bootstrap estimates of standard error, confidence intervals and the application of the bootstrap principle to do Monte Carlo bootstrap approximations in a wide variety of complex and previously intractable problems.br /br /


5 out of 5 stars awesome collection of greatest papers in statistics!   September 15, 2005
 8 out of 8 found this review helpful

Knuth said, garbage in garbage out. These three volumes are absolutely treasure of statistics, forever. The excellent papers in the past 110 years are collected and introduced. Whatever for students or researchers, they are definitely valuable to be at hand.br /br /[1] The original papers are attached. Do you remember Abel said, Read the masters', not their pupils'?br /[2] For each important paper, there is an introduction written by the real experts of this domain.br /[3] This is a real awesome book that leads you to overview the history of statistics.br /[4] You can find a surprise of good price somewhere on campusi.com if you need all the three volumes.

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