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Core Statistics

Core Statistics PDF Author: Simon N. Wood
Publisher: Cambridge University Press
ISBN: 1107071054
Category : Business & Economics
Languages : en
Pages : 259

Book Description
Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Core Statistics

Core Statistics PDF Author: Simon N. Wood
Publisher: Cambridge University Press
ISBN: 1107071054
Category : Business & Economics
Languages : en
Pages : 259

Book Description
Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Theoretical Statistics

Theoretical Statistics PDF Author: Robert W. Keener
Publisher: Springer Science & Business Media
ISBN: 0387938397
Category : Mathematics
Languages : en
Pages : 543

Book Description
Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix.

Bayesian Core: A Practical Approach to Computational Bayesian Statistics

Bayesian Core: A Practical Approach to Computational Bayesian Statistics PDF Author: Jean-Michel Marin
Publisher: Springer Science & Business Media
ISBN: 0387389792
Category : Computers
Languages : en
Pages : 265

Book Description
This Bayesian modeling book provides the perfect entry for gaining a practical understanding of Bayesian methodology. It focuses on standard statistical models and is backed up by discussed real datasets available from the book website.

Understanding Statistics and Experimental Design

Understanding Statistics and Experimental Design PDF Author: Michael H. Herzog
Publisher: Springer
ISBN: 3030034992
Category : Science
Languages : en
Pages : 146

Book Description
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

Asymptotic Statistics

Asymptotic Statistics PDF Author: A. W. van der Vaart
Publisher: Cambridge University Press
ISBN: 9780521784504
Category : Mathematics
Languages : en
Pages : 470

Book Description
This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master s level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.

Core Concepts in Data Analysis: Summarization, Correlation and Visualization

Core Concepts in Data Analysis: Summarization, Correlation and Visualization PDF Author: Boris Mirkin
Publisher: Springer Science & Business Media
ISBN: 0857292870
Category : Computers
Languages : en
Pages : 402

Book Description
Core Concepts in Data Analysis: Summarization, Correlation and Visualization provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate different aspects of data (decision trees, linear rules, neuron networks, and Bayes rule). Boris Mirkin takes an unconventional approach and introduces the concept of multivariate data summarization as a counterpart to conventional machine learning prediction schemes, utilizing techniques from statistics, data analysis, data mining, machine learning, computational intelligence, and information retrieval. Innovations following from his in-depth analysis of the models underlying summarization techniques are introduced, and applied to challenging issues such as the number of clusters, mixed scale data standardization, interpretation of the solutions, as well as relations between seemingly unrelated concepts: goodness-of-fit functions for classification trees and data standardization, spectral clustering and additive clustering, correlation and visualization of contingency data. The mathematical detail is encapsulated in the so-called “formulation” parts, whereas most material is delivered through “presentation” parts that explain the methods by applying them to small real-world data sets; concise “computation” parts inform of the algorithmic and coding issues. Four layers of active learning and self-study exercises are provided: worked examples, case studies, projects and questions.

High-Dimensional Statistics

High-Dimensional Statistics PDF Author: Martin J. Wainwright
Publisher: Cambridge University Press
ISBN: 1108498027
Category : Business & Economics
Languages : en
Pages : 571

Book Description
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

Core Statistical Concepts With Excel®

Core Statistical Concepts With Excel® PDF Author: Gregory J. Privitera
Publisher: SAGE Publications
ISBN: 1544309074
Category : Psychology
Languages : en
Pages : 378

Book Description
Core Statistical Concepts with Excel® connects statistical concepts to applications with Excel® using practical research examples. The text jointly promotes an understanding of Excel® and a deeper knowledge of core concepts through practice. Authors Gregory J. Privitera and Darryl Mayeaux provide students step-by-step instruction for using Excel® software as a useful tool not only to manage but also analyze data—all through the use of key themes, features, and pedagogy: an emphasis on student learning, a focus on current research, and integration of Excel® to introduce statistical concepts.

Statistical Inference as Severe Testing

Statistical Inference as Severe Testing PDF Author: Deborah G. Mayo
Publisher: Cambridge University Press
ISBN: 1108563309
Category : Mathematics
Languages : en
Pages : 503

Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Mathematical Finance

Mathematical Finance PDF Author: Nikolai Dokuchaev
Publisher: Routledge
ISBN: 1134121970
Category : Business & Economics
Languages : en
Pages : 234

Book Description
Written in a rigorous yet logical and easy to use style, spanning a range of disciplines, including business, mathematics, finance and economics, this comprehensive textbook offers a systematic, self-sufficient yet concise presentation of the main topics and related parts of stochastic analysis and statistical finance that are covered in the majori