Introductory Statistics With R

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Introductory Statistics With R

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Author : Peter Dalgaard
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-15

Introductory Statistics With R written by Peter Dalgaard and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-15 with Mathematics categories.

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

Using R For Introductory Statistics

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Author : John Verzani
language : en
Publisher: CRC Press
Release Date : 2018-10-03

Using R For Introductory Statistics 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 2018-10-03 with Computers 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.

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.

Introduction To Probability And Statistics Using R

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Author : G. Jay Kerns
language : en
Publisher: Lulu.com
Release Date : 2010-01-10

Introduction To Probability And Statistics Using R written by G. Jay Kerns and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-10 with Education categories.

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.

Introductory Statistics

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Author : William B. Ware
language : en
Publisher: Routledge
Release Date : 2013-02-15

Introductory Statistics written by William B. Ware and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-15 with Education categories.

This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. A conceptual approach, built around common issues and problems rather than statistical techniques, allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Wherever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following. Conceptual Focus – The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures. Problems and Cases – Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output. Continuity of Examples – A master data set containing nearly all of the data used in the book’s examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text. Companion Website – A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises. Field Tested – The manuscript has been field tested for three years at two leading institutions.

Introductory Statistics For The Behavioral Sciences

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Author : R. Brooke Lea
language : en
Publisher: John Wiley & Sons
Release Date : 2025-09-05

Introductory Statistics For The Behavioral Sciences written by R. Brooke Lea 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 2025-09-05 with Psychology categories.

The accessible, hands-on statistics textbook that behavioral science students and instructors trust Introductory Statistics for the Behavioral Sciences is a respected, practical textbook that offers carefully crafted exercises to support the teaching and learning of statistics. This revised eighth edition presents all the topics students in the behavioral sciences need in a uniquely accessible format, making statistics feel relevant and approachable. With fictitious yet realistic examples that reappear throughout the chapter, students can follow a continuous narrative that helps them engage with and internalize the content. User-friendly integration with SPSS software enables readers to gain hands-on experience with the application of theoretical concepts. Exercises at the end of each chapter, with additional practice in the online study guide, give students the repetition they need to fully comprehend the material. After working through this textbook, students will understand, not only the what, but also the why of statistical analysis. Get plain-English explanations of statistical concepts and procedures important in behavioral sciences research Learn from relatable examples and exercises focused on psychology, sociology, and other behavioral science Work through well-crafted exercises designed to enhance your understanding of the material Get clear instructions on how to perform statistical procedures with the industry-standard SPSS software Online resources for instructors include a test bank, chapter quizzes, and PowerPoint slides. Introductory Statistics for the Behavioral Sciences also includes a student website containing additional basic math coverage, math review exercises, a study guide, a set of additional SPSS exercises, and downloadable data sets.

Categorical Data Analysis And Multilevel Modeling Using R

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Author : Xing Liu
language : en
Publisher: SAGE Publications
Release Date : 2022-02-25

Categorical Data Analysis And Multilevel Modeling Using R written by Xing Liu and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Social Science categories.

Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.

Introductory Statistics With R

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Author : Max Walker
language : en
Publisher:
Release Date : 2018

Introductory Statistics With R written by Max Walker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with R (Computer program language) categories.

Solutions Manual For Using R For Introductory Statistics

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Author : John Verzani
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2004-11

Solutions Manual For Using R For Introductory Statistics written by John Verzani and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11 with categories.

Mathematical Statistics With Resampling And R

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Author : Laura M. Chihara
language : en
Publisher: John Wiley & Sons
Release Date : 2012-09-05

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 2012-09-05 with Mathematics categories.

This book bridges 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. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques. The book begins by introducing permutation tests and bootstrap methods, motivating classical inference methods. Striking a balance between theory, computing, and applications, the authors explore additional topics such as: Exploratory data analysis Calculation of sampling distributions The Central Limit Theorem Monte Carlo sampling Maximum likelihood estimation and properties of estimators Confidence intervals and hypothesis tests Regression Bayesian methods Throughout the book, case studies on diverse subjects such as flight delays, birth weights of babies, and telephone company repair times illustrate the relevance of the real-world applications of the discussed material. Key definitions and theorems of important probability distributions are collected at the end of the book, and a related website is also available, featuring additional material including data sets, R scripts, and helpful teaching hints. Mathematical Statistics with Resampling and R is an excellent book for courses on mathematical statistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians working in the areas of business, economics, biostatistics, and public health who utilize resampling methods in their everyday work.