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## OpenIntro Statistics

The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
## OpenIntro Statistics

The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
## OpenIntro Statistics

## Introduction to Statistical Data Analysis for the Life Sciences, Second Edition

A Hands-On Approach to Teaching Introductory Statistics Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets. New to the Second Edition A new chapter on non-linear regression models A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken Additional exercises in most chapters A summary of statistical formulas related to the specific designs used to teach the statistical concepts This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.
## An R and S-Plus® Companion to Multivariate Analysis

Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.
## The Book of R

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.
## The Elements of Statistical Learning

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
## Introductory Statistics

Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises. Includes new section on Pareto distribution and the 80-20 rule, Benford’s law, odds, joint distribution and correlation, logistic regression, A-B testing, and examples from the world of analytics and big data Comprehensive edition that includes the most commonly used statistical software packages (SAS, SPSS, Minitab), ISM, SSM, and an online graphing calculator manual Presents a unique, historical perspective, profiling prominent statisticians and historical events to motivate learning by including interest and context Provides exercises and examples that help guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud
## The R Student Companion

R is the amazing, free, open-access software package for scientific graphs and calculations used by scientists worldwide. The R Student Companion is a student-oriented manual describing how to use R in high school and college science and mathematics courses. Written for beginners in scientific computation, the book assumes the reader has just some high school algebra and has no computer programming background. The author presents applications drawn from all sciences and social sciences and includes the most often used features of R in an appendix. In addition, each chapter provides a set of computational challenges: exercises in R calculations that are designed to be performed alone or in groups. Several of the chapters explore algebra concepts that are highly useful in scientific applications, such as quadratic equations, systems of linear equations, trigonometric functions, and exponential functions. Each chapter provides an instructional review of the algebra concept, followed by a hands-on guide to performing calculations and graphing in R. R is intuitive, even fun. Fantastic, publication-quality graphs of data, equations, or both can be produced with little effort. By integrating mathematical computation and scientific illustration early in a student’s development, R use can enhance one's understanding of even the most difficult scientific concepts. While R has gained a strong reputation as a package for statistical analysis, The R Student Companion approaches R more completely as a comprehensive tool for scientific computing and graphing.
## Introduction to Probability and Statistics

Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, continues to blend the best of its proven, error-free coverage with new innovations. Written for the higher end of the traditional introductory statistics market, the book takes advantage of modern technology--including computational software and interactive visual tools--to facilitate statistical reasoning as well as the interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to describe real sets of data meaningfully, what the statistical tests mean in terms of their practical applications, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. The new edition retains the statistical integrity, examples, exercises, and exposition that have made this text a market leader--and builds upon this tradition of excellence with new technology integration. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
## Mathematical Statistics and Data Analysis

This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings.
## Interactive Statistics

This volume takes a hands-on approach to the introduction of basic statistical methods, using a highly interactive method. Readers are taught to ask "why" and think like a statistician to find the logical solution. With its strong emphasis on data analysis, the book gives readers the skills to understand and interpret a variety of statistical results. Provides an overview of the basic components of decision-making and using statistical ideas. Helps readers master the language of statistics, the importance of a p-value, and the meaning of statistical significance. Includes coverage of current topics such as power of the test and effect size, bootstrap, and blocking designs in experiments. Usesexamples frombusiness, sports, economics, and more to address a wide range of interests. Includes chapter-ending TI Quick Steps for using calculators to enter, manipulate, and plot data. For anyone interested in learning more about statistics.
## Intro Stats

For courses in Introductory Statistics. Encourages statistical thinking using technology, innovative methods, and a sense of humor Inspired by the 2016 GAISE Report revision, Intro Stats, 5th Edition by De Veaux/Velleman/Bock uses innovative strategies to help students think critically about data - while maintaining the book's core concepts, coverage, and most importantly, readability. By using technology and simulations to demonstrate variability at critical points throughout the course, the authors make it easier for students to understand more complicated statistical later in the course (such as the Central Limit Theorem). In addition, students get more exposure to large data sets and multivariate thinking, which better prepares them to be critical consumers of statistics in the 21st century. The 5th Edition's approach to teaching intro stats is revolutionary, while retaining its lively tone and popular features such as Think/Show/Tell examples. Also available with MyLab Statistics Used by nearly one million students a year, MyLab(tm) Statistics is the world's leading online program for teaching and learning statistics. MyLab Statistics delivers assessment, tutorials, and multimedia resources that provide engaging and personalized experiences for each student, so learning can happen in any environment. Each course is developed to accompany Pearson's best-selling content, authored by thought leaders across the statistics curriculum, and can be easily customized to fit any course format. Note: You are purchasing a standalone product; MyLab Statistics does not come packaged with this content. Students, if interested in purchasing this title with MyLab Statistics, ask your instructor to confirm the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Statistics, search for: 0134210239 / 9780134210230 Intro Stats Plus NEW MyLab Statistics with Pearson eText - Access Card Package, 5/e Package consists of: 0134210220 / 9780134210223 Intro Stats, 5/e 0134768361 / 9780134768366 MyLab Statistics with Pearson eText - Standalone Access Card - for Intro Stats 5/e
## Introductory Statistics

Introductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them. Coverage and Scope Chapter 1 Sampling and Data Chapter 2 Descriptive Statistics Chapter 3 Probability Topics Chapter 4 Discrete Random Variables Chapter 5 Continuous Random Variables Chapter 6 The Normal Distribution Chapter 7 The Central Limit Theorem Chapter 8 Confidence Intervals Chapter 9 Hypothesis Testing with One Sample Chapter 10 Hypothesis Testing with Two Samples Chapter 11 The Chi-Square Distribution Chapter 12 Linear Regression and Correlation Chapter 13 F Distribution and One-Way ANOVA
## Special Relativity

Written in a clear, informal style, this text explores the most accessible of the 20th century revolutions in physics. It allows readers to build up physical intuition for what is going on, before presenting concise mathematical descriptions. It contains many applications and numerous illustrations, examples and problems.
## Human Resource Strategy

What is human resource strategy? How are human resources strategies formulated and how can we explain the variance between what is espoused and what is actually implemented? What impact – if any – does human resource strategy have on the organization’s "bottom line," and how can this impact be explained? Is there one best HR strategy for all firms, or is the impact of HR strategy on performance contingent on some set of organizational, technological or environmental factors? Human Resource Strategy, 2nd edition, provides an overview of the academic and practitioner responses to these and other questions. Applying an integrative framework, the authors review 30 years’ worth of empirical and theoretical research in an attempt to reconcile often-conflicting conceptual models and competing empirical results. Complex theoretical models and scientific findings are presented in an accessible and relevant way, in the context of the strategic decisions that executives are forced to make on a regular basis. This new edition features an updated literature review, coverage of the latest challenges to HR strategy, new mini-cases, discussion questions, additional examples, and an emphasis on the strategic implications of the research, making it an ideal resource for students and practitioners alike.
## Introduction to Probability and Statistics Using R

## Cognitive Science

In Cognitive Science 3e Friedenberg and Silverman provide a solid understanding of the major theoretical and empirical contributions of cognitive science. Their text, thoroughly updated for this new third edition, describes the major theories of mind as well as the major experimental results that have emerged within each cognitive science discipline. Throughout history, different fields of inquiry have attempted to understand the great mystery of mind and answer questions like: What is the mind? How do we see, think, and remember? Can we create machines that are conscious and capable of self-awareness? This books examines these questions and many more. Focusing on the approach of a particular cognitive science field in each chapter, the authors describe its methodology, theoretical perspective, and findings and then offer a critical evaluation of the field. Features: Offers a wide-ranging, comprehensive, and multidisciplinary introduction to the field of cognitive science and issues of mind. Interdisciplinary Crossroads” sections at the end of each chapter focus on research topics that have been investigated from multiple perspectives, helping students to understand the link between varying disciplines and cognitive science. End-of-chapter “Summing Up” sections provide a concise summary of the major points addressed in each chapter to facilitate student comprehension and exam preparation “Explore More” sections link students to the Student Study Site where the authors have provided activities to help students more quickly master course content and prepare for examinations Supplements: A password-protected Instructor’s Resource contains PowerPoint lectures, a test bank and other pedagogical material.The book's Study Site features Web links, E-flash cards, and interactive quizzes.
## Statistics for the Behavioral Sciences

The engaging Third Edition of Statistics for the Behavioral Sciences shows students that statistics can be understandable, interesting, and relevant to their daily lives. Using a conversational tone, award-winning teacher and author Gregory J. Privitera speaks to the reader as researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills when working through carefully developed problems and exercises that include current research and seamless integration of SPSS. This edition will not only prepare students to be lab-ready, but also give them the confidence to use statistics to summarize data and make decisions about behavior.

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Author: David Diez,Christopher Barr,Mine Çetinkaya-Rundel

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