The Statistical Sleuth A Course In Methods Of Data Analysis
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The Statistical Sleuth
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Author : Fred L. Ramsey
language : en
Publisher: Duxbury Resource Center
Release Date : 2002
The Statistical Sleuth written by Fred L. Ramsey and has been published by Duxbury Resource Center this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Mathematical statistics categories.
Prepare for exams and succeed in your statistics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, 2nd Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.
The Statistical Sleuth A Course In Methods Of Data Analysis
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Author : Fred Ramsey
language : en
Publisher: Cengage Learning
Release Date : 2012-05-02
The Statistical Sleuth A Course In Methods Of Data Analysis written by Fred Ramsey and has been published by Cengage Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-02 with Mathematics categories.
THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, Third Edition offers an appealing treatment of general statistical methods that takes full advantage of the computer, both as a computational and an analytical tool. The material is independent of any specific software package, and prominently treats modeling and interpretation in a way that goes beyond routine patterns. The book focuses on a serious analysis of real case studies, strategies and tools of modern statistical data analysis, the interplay of statistics and scientific learning, and the communication of results. With interesting examples, real data, and a variety of exercise types (conceptual, computational, and data problems), the authors get students excited about statistics. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
The Statistical Sleuth
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Author : Fred L. Ramsey
language : en
Publisher:
Release Date : 2008
The Statistical Sleuth written by Fred L. Ramsey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Mathematical statistics categories.
The Statistical Sleuth
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Author : Fred Ramsey
language : en
Publisher:
Release Date : 1997
The Statistical Sleuth written by Fred Ramsey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Using R For Introductory Statistics Second Edition
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Author : John Verzani
language : en
Publisher: CRC Press
Release Date : 2014-06-26
Using R For Introductory Statistics Second Edition written by John Verzani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-26 with Mathematics categories.
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
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.
Discrete Data Analysis With R
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Author : Michael Friendly
language : en
Publisher: CRC Press
Release Date : 2015-12-16
Discrete Data Analysis With R written by Michael Friendly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-16 with Mathematics categories.
An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth
Beyond Multiple Linear Regression
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Author : Paul Roback
language : en
Publisher: CRC Press
Release Date : 2021-01-14
Beyond Multiple Linear Regression written by Paul Roback and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Mathematics categories.
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. A solutions manual for all exercises is available to qualified instructors at the book’s website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors’ GitHub repo (https://github.com/proback/BeyondMLR)