OpenIntro Statistics

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

Publisher: N.A

ISBN: 9781943450046

Category:

Page: N.A

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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

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

Publisher: N.A

ISBN: 9781943450039

Category:

Page: N.A

View: 776

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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.

Advanced High School Statistics

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

Publisher: N.A

ISBN: 9781943450008

Category:

Page: N.A

View: 1470

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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.The future for OpenIntro depends on the involvement and enthusiasm of our community. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Introduction to Statistics Through Resampling Methods and R

Author: Phillip I. Good

Publisher: John Wiley & Sons

ISBN: 1118497570

Category: Mathematics

Page: 224

View: 1495

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A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.

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

Author: Claus Thorn Ekstrom,Helle Sørensen

Publisher: CRC Press

ISBN: 1482238934

Category: Mathematics

Page: 526

View: 3270

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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 Introduction to Statistics with Python

With Applications in the Life Sciences

Author: Thomas Haslwanter

Publisher: Springer

ISBN: 3319283162

Category: Computers

Page: 278

View: 4275

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This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.

An R and S-Plus® Companion to Multivariate Analysis

Author: Brian S. Everitt

Publisher: Springer Science & Business Media

ISBN: 1846281245

Category: Mathematics

Page: 221

View: 6995

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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.

Statistics

Fourth International Student Edition

Author: David Freedman,Robert Pisani,Roger Purves

Publisher: W. W. Norton & Company

ISBN: 0393930432

Category: Mathematics

Page: 576

View: 3522

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The Fourth Edition has been carefully revised and updated to reflect current data.

Post-Truth

Author: Lee McIntyre

Publisher: MIT Press

ISBN: 0262535041

Category: Philosophy

Page: 240

View: 2027

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Are we living in a post-truth world, where "alternative facts" replace actual facts and feelings have more weight than evidence? How did we get here? In this volume in the MIT Press Essential Knowledge series, Lee McIntyre traces the development of the post-truth phenomenon from science denial through the rise of "fake news," from our psychological blind spots to the public's retreat into "information silos." What, exactly, is post-truth? Is it wishful thinking, political spin, mass delusion, bold-faced lying? McIntyre analyzes recent examples -- claims about inauguration crowd size, crime statistics, and the popular vote -- and finds that post-truth is an assertion of ideological supremacy by which its practitioners try to compel someone to believe something regardless of the evidence. Yet post-truth didn't begin with the 2016 election; the denial of scientific facts about smoking, evolution, vaccines, and climate change offers a road map for more widespread fact denial. Add to this the wired-in cognitive biases that make us feel that our conclusions are based on good reasoning even when they are not, the decline of traditional media and the rise of social media, and the emergence of fake news as a political tool, and we have the ideal conditions for post-truth. McIntyre also argues provocatively that the right wing borrowed from postmodernism -- specifically, the idea that there is no such thing as objective truth -- in its attacks on science and facts. McIntyre argues that we can fight post-truth, and that the first step in fighting post-truth is to understand it.

Introductory Statistics

Author: Barbara Illowsky,Susan Dean

Publisher: N.A

ISBN: 9789888407309

Category: Education

Page: 906

View: 9113

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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

An Introduction to Statistical Learning

with Applications in R

Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani

Publisher: Springer Science & Business Media

ISBN: 1461471389

Category: Mathematics

Page: 426

View: 5142

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

The Book of R

A First Course in Programming and Statistics

Author: Tilman M. Davies

Publisher: No Starch Press

ISBN: 1593277792

Category: Computers

Page: 832

View: 9871

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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.

Statistics from A to Z

Confusing Concepts Clarified

Author: Andrew Jawlik

Publisher: John Wiley & Sons

ISBN: 1119272033

Category: MATHEMATICS

Page: 448

View: 2504

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Of Keys to UnderstandingExplanation; ANOVA - Part 2 (of 4): How it Does it; Summary of Keys to Understanding; Explanation; ANOVA - Part 3 (OF 4): 1-Way (AKA Single Factor); Summary of Keys to Understanding; Explanation; ANOVA - Part 4 (OF 4): 2-Way (AKA 2-Factor); Summary of Keys to Understanding; Explanation; ANOVA vs. Regression; Summary of Keys to Understanding; Explanation; Binomial Distribution; Summary of Keys to Understanding; Explanation; Charts/Graphs/Plots - Which to Use When; Explanation; Correlation; Exploratory Data Analysis (EDA); Residual Analysis Of Keys to UnderstandingExplanation; Mean; Confidence Intervals for the Mean and Proportion for Non-Normal Data.; Proportion; Variance; Control Charts - Part 1 (of 2): General Concepts and Principles; Summary of Keys to Understanding; Explanation; Control Charts - Part 2 (of 2): Which to Use When; Summary of Keys to Understanding; Explanation; Correlation - Part 1 (of 2); Summary of Keys to Understanding; Explanation; Correlation - Part 2 (of 2); Summary of Keys to Understanding; Explanation; Critical Value; Summary of Keys to Understanding; Explanation; 1-Sided, Right-Tailed.

Fundamentals of Business (black and White)

Author: Stephen J. Skripak

Publisher: N.A

ISBN: 9780997920116

Category:

Page: 442

View: 3713

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(Black & White version) Fundamentals of Business was created for Virginia Tech's MGT 1104 Foundations of Business through a collaboration between the Pamplin College of Business and Virginia Tech Libraries. This book is freely available at: http://hdl.handle.net/10919/70961 It is licensed with a Creative Commons-NonCommercial ShareAlike 3.0 license.

R Graphics Cookbook

Author: Winston Chang

Publisher: "O'Reilly Media, Inc."

ISBN: 1449316956

Category: Computers

Page: 396

View: 1286

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"Practical recipes for visualizing data"--Cover.

Computer Security Literacy

Staying Safe in a Digital World

Author: Douglas Jacobson,Joseph Idziorek

Publisher: CRC Press

ISBN: 1439856192

Category: Computers

Page: 368

View: 1081

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Computer users have a significant impact on the security of their computer and personal information as a result of the actions they perform (or do not perform). Helping the average user of computers, or more broadly information technology, make sound security decisions, Computer Security Literacy: Staying Safe in a Digital World focuses on practical security topics that users are likely to encounter on a regular basis. Written for nontechnical readers, the book provides context to routine computing tasks so that readers better understand the function and impact of security in everyday life. The authors offer practical computer security knowledge on a range of topics, including social engineering, email, and online shopping, and present best practices pertaining to passwords, wireless networks, and suspicious emails. They also explain how security mechanisms, such as antivirus software and firewalls, protect against the threats of hackers and malware. While information technology has become interwoven into almost every aspect of daily life, many computer users do not have practical computer security knowledge. This hands-on, in-depth guide helps anyone interested in information technology to better understand the practical aspects of computer security and successfully navigate the dangers of the digital world.

Linear Algebra

A Course for Physicists and Engineers

Author: Arak M. Mathai,Hans J. Haubold

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110562502

Category: Mathematics

Page: 467

View: 7075

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In order not to intimidate students by a too abstract approach, this textbook on linear algebra is written to be easy to digest by non-mathematicians. It introduces the concepts of vector spaces and mappings between them without dwelling on statements such as theorems and proofs too much. It is also designed to be self-contained, so no other material is required for an understanding of the topics covered. As the basis for courses on space and atmospheric science, remote sensing, geographic information systems, meteorology, climate and satellite communications at UN-affiliated regional centers, various applications of the formal theory are discussed as well. These include differential equations, statistics, optimization and some engineering-motivated problems in physics. Contents Vectors Matrices Determinants Eigenvalues and eigenvectors Some applications of matrices and determinants Matrix series and additional properties of matrices