Statistics

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Published:
July 25, 2014
Editor(s):
Charu C. Aggarwal
Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data 
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Published:
July 24, 2014
Author(s):
Joseph K. Blitzstein, Jessica Hwang
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google 
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Pack - Book & eBook
Published:
July 22, 2014
Author(s):
John Chen
Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities 
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Published:
July 22, 2014
Author(s):
Mark Chang
Principles of Scientific Methods focuses on the fundamental principles behind scientific methods. The book refers to "science" in a broad sense, including natural science, physics, mathematics, statistics, social science, political science, and engineering science. A principle is often abstract and 
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Paperback
Published:
July 17, 2014
Author(s):
Brady T. West, Kathleen B. Welch, Andrzej T Galecki
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues 
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Published:
July 17, 2014
Author(s):
Ken Kleinman, Nicholas J. Horton
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, 
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Published:
July 14, 2014
Author(s):
Marc Lavielle
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can 
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Published:
July 07, 2014
Author(s):
Nicholas T. Longford
There is no shortage of incentives to study and reduce poverty in our societies. Poverty is studied in economics and political sciences, and population surveys are an important source of information about it. The design and analysis of such surveys is principally a statistical subject matter and 
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Published:
July 07, 2014
Author(s):
Patrick Laurie Davies
The First Detailed Account of Statistical Analysis That Treats Models as Approximations The idea of truth plays a role in both Bayesian and frequentist statistics. The Bayesian concept of coherence is based on the fact that two different models or parameter values cannot both be true. Frequentist 
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Published:
July 01, 2014
Author(s):
Julian J. Faraway
A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with 
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Hardback

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