The Basic Practice Of Statistics 3e Splus Cd Splus Guide
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The Basic Practice Of Statistics 3e Splus Cd Splus Guide
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Author : David S. Moore
language : en
Publisher: W H Freeman & Company
Release Date : 2003-12-18
The Basic Practice Of Statistics 3e Splus Cd Splus Guide written by David S. Moore and has been published by W H Freeman & Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-18 with Mathematics categories.
The Basic Practice Of Statistics 3e Splus Guide
DOWNLOAD
Author : David S. Moore
language : en
Publisher: W H Freeman & Company
Release Date : 2003-12-18
The Basic Practice Of Statistics 3e Splus Guide written by David S. Moore and has been published by W H Freeman & Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-18 with Mathematics categories.
Statistics With Confidence
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Author : Douglas Altman
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-03
Statistics With Confidence written by Douglas Altman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-03 with Medical categories.
This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
Statistics
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Author : Michael J. Crawley
language : en
Publisher: John Wiley & Sons
Release Date : 2005-05-06
Statistics written by Michael J. Crawley and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-06 with Mathematics categories.
Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
Mathematical Statistics With Resampling And R
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Author : Laura M. Chihara
language : en
Publisher: John Wiley & Sons
Release Date : 2018-09-17
Mathematical Statistics With Resampling And R written by Laura M. Chihara and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-17 with Mathematics categories.
This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.
Applied Linear Statistical Models
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Author : Michael H. Kutner
language : en
Publisher: McGraw-Hill Education
Release Date : 2005
Applied Linear Statistical Models written by Michael H. Kutner and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Analysis of variance categories.
Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
An Introduction To Categorical Data Analysis
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Author : Alan Agresti
language : en
Publisher: John Wiley & Sons
Release Date : 2018-11-20
An Introduction To Categorical Data Analysis written by Alan Agresti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-20 with Mathematics categories.
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
The Basic Practice Of Statistics
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Author : Moore
language : en
Publisher:
Release Date : 2001-09-01
The Basic Practice Of Statistics written by Moore and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-09-01 with categories.
Statistics For Linguists An Introduction Using R
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Author : Bodo Winter
language : en
Publisher: Routledge
Release Date : 2019-10-30
Statistics For Linguists An Introduction Using R written by Bodo Winter and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-30 with Education categories.
Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.
Analyzing Linguistic Data
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Author : R. H. Baayen
language : en
Publisher: Cambridge University Press
Release Date : 2008-03-06
Analyzing Linguistic Data written by R. H. Baayen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-06 with Language Arts & Disciplines categories.
Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.