Practical Statistics in R for Comparing Groups PDF Download
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Author: Alboukadel Kassambara
Publisher:
ISBN: 9781712330883
Category :
Languages : en
Pages : 206
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Book Description
This R Statistics book provides a solid step-by-step practical guide to statistical inference for comparing groups means using the R software. Additionally, we developed an R package named rstatix, which provides a simple and intuitive pipe-friendly framework, coherent with the `tidyverse` design philosophy, for computing the most common R statistical analyses, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses, outliers identification and more. This book is designed to get you doing the statistical tests in R as quick as possible. The book focuses on implementation and understanding of the methods, without having to struggle through pages of mathematical proofs. You will be guided through the steps of summarizing and visualizing the data, checking the assumptions and performing statistical tests in R, interpreting and reporting the results. The main parts of the book include: PART I. Statistical tests and assumptions for the comparison of groups means; PART II. comparing two means (t-test, Wilcoxon test, Sign test); PART III. comparing multiple means (ANOVA - Analysis of Variance for independent measures, repeated measures ANOVA, mixed ANOVA, ANCOVA and MANOVA, Kruskal-Wallis test and Friedman test).
Author: Alboukadel Kassambara
Publisher:
ISBN: 9781712330883
Category :
Languages : en
Pages : 206
Get Book Here
Book Description
This R Statistics book provides a solid step-by-step practical guide to statistical inference for comparing groups means using the R software. Additionally, we developed an R package named rstatix, which provides a simple and intuitive pipe-friendly framework, coherent with the `tidyverse` design philosophy, for computing the most common R statistical analyses, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses, outliers identification and more. This book is designed to get you doing the statistical tests in R as quick as possible. The book focuses on implementation and understanding of the methods, without having to struggle through pages of mathematical proofs. You will be guided through the steps of summarizing and visualizing the data, checking the assumptions and performing statistical tests in R, interpreting and reporting the results. The main parts of the book include: PART I. Statistical tests and assumptions for the comparison of groups means; PART II. comparing two means (t-test, Wilcoxon test, Sign test); PART III. comparing multiple means (ANOVA - Analysis of Variance for independent measures, repeated measures ANOVA, mixed ANOVA, ANCOVA and MANOVA, Kruskal-Wallis test and Friedman test).
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
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Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522
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Book Description
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.
Author: David Kremelberg
Publisher: SAGE Publications
ISBN: 150631791X
Category : Social Science
Languages : en
Pages : 529
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Book Description
Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.
Author: Michael J. Crawley
Publisher: John Wiley & Sons
ISBN: 9780470515068
Category : Mathematics
Languages : en
Pages : 953
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Book Description
The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
Author: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833
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Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Author: G. Jay Kerns
Publisher: Lulu.com
ISBN: 0557249791
Category : Education
Languages : en
Pages : 388
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Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author: Ruth Ravid
Publisher: Rowman & Littlefield
ISBN: 1538191717
Category : Education
Languages : en
Pages : 335
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Book Description
Practical Statistics for Educators, Seventh Edition, is a clear and easy-to follow book written specifically for education students in introductory statistics and action research courses. It is also an invaluable resource and guidebook for educational practitioners who wish to study their own settings and for those involved in program evaluation. The book’s focus is on essential concepts in educational statistics, understanding when to use various statistical tests, and learning how to interpret results. This book introduces education students and practitioners to the use of parametric and nonparametric statistics in education, and basic concepts in statistics are explained in clear language. Formulas and equations are used sparingly, and readers are not required to do any computations. The book also includes a discussion of testing, test score interpretation, reliability, and validity. A chapter on survey design and analysis provides readers with examples that demonstrate how the different statistical tests introduced in the book can be used to analyze survey data. An extensive study guide at the end of the book provides an opportunity to review all the information that was presented in the book; the guide includes an answer key with a clear explanation of each correct answer. Throughout this text, examples taken from the field of education serve to illustrate the various concepts, terms, statistical tests, and data interpretations.
Author: Rand R. Wilcox
Publisher: Gulf Professional Publishing
ISBN: 9780127515410
Category : Mathematics
Languages : en
Pages : 688
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Book Description
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana
Author: Jeff Sauro
Publisher: Morgan Kaufmann
ISBN: 0128025484
Category : Computers
Languages : en
Pages : 374
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Book Description
Quantifying the User Experience: Practical Statistics for User Research, Second Edition, provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website? This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. - Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practices - Includes new and revised information on standardized usability questionnaires - Includes a completely new chapter introducing correlation, regression, and analysis of variance - Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing data - Recommends ways for researchers and practitioners to communicate results to stakeholders in plain English
