Statistics from A to Z

Author: Andrew A. Jawlik
Publisher: John Wiley & Sons
ISBN: 1119272009
Format: PDF, ePub
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Statistics is confusing, even for smart, technically competent people. And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are: • Easy to Understand: Uses unique “graphics that teach” such as concept flow diagrams, compare-and-contrast tables, and even cartoons to enhance “rememberability.” • Easy to Use: Alphabetically arranged, like a mini-encyclopedia, for easy lookup on the job, while studying, or during an open-book exam. • Wider Scope: Covers Statistics I and Statistics II and Six Sigma Black Belt, adding such topics as control charts and statistical process control, process capability analysis, and design of experiments. As a result, this book will be useful for business professionals and industrial engineers in addition to students and professionals in the social and physical sciences. In addition, each of the 60+ concepts is covered in one or more articles. The 75 articles in the book are usually 5–7 pages long, ensuring that things are presented in “bite-sized chunks.” The first page of each article typically lists five “Keys to Understanding” which tell the reader everything they need to know on one page. This book also contains an article on “Which Statistical Tool to Use to Solve Some Common Problems”, additional “Which to Use When” articles on Control Charts, Distributions, and Charts/Graphs/Plots, as well as articles explaining how different concepts work together (e.g., how Alpha, p, Critical Value, and Test Statistic interrelate). ANDREW A. JAWLIK received his B.S. in Mathematics and his M.S. in Mathematics and Computer Science from the University of Michigan. He held jobs with IBM in marketing, sales, finance, and information technology, as well as a position as Process Executive. In these jobs, he learned how to communicate difficult technical concepts in easy - to - understand terms. He completed Lean Six Sigma Black Belt coursework at the IASSC - accredited Pyzdek Institute. In order to understand the confusing statistics involved, he wrote explanations in his own words and graphics. Using this material, he passed the certification exam with a perfect score. Those statistical explanations then became the starting point for this book.

Statistics in Plain English

Author: Timothy C. Urdan
Publisher: Psychology Press
ISBN: 0805852417
Format: PDF, Docs
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This book is meant to be a supplement to a more detailed statistics textbook, such as that recommended for a statistics course in the social sciences. Also, as a reference book to refresh your memory about statistical concepts.

Think Stats

Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491907371
Format: PDF, ePub, Mobi
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If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data

Statistics in a Nutshell

Author: Sarah Boslaugh
Publisher: "O'Reilly Media, Inc."
ISBN: 1449316824
Format: PDF, ePub, Mobi
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A clear and concise introduction and reference for anyone new to the subject of statistics.

An Introduction to Statistical Learning

Author: Gareth James
Publisher: Springer Science & Business Media
ISBN: 1461471389
Format: PDF
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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.

Understandable Statistics Concepts and Methods

Author: Charles Henry Brase
Publisher: Cengage Learning
ISBN: 1337119911
Format: PDF, ePub, Mobi
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UNDERSTANDABLE STATISTICS: CONCEPTS AND METHODS, Twelfth Edition, is a thorough yet accessible program designed to help you overcome any apprehensions you may have about statistics and to master the subject. The authors provide clear guidance and informal advice while showing you the links between statistics and the world. To reinforce this approach—and make the material interesting as well as easier to understand—the book integrates real-life data from a variety of sources, including journals, periodicals, newspapers, and the Internet. You'll also have opportunities to develop your critical-thinking and statistical literacy skills through special features and exercises throughout the text. The use of graphing calculators, Excel, Minitab, Minitab ExpressTM, and SPSS is covered, although not required. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Causal Inference in Statistics

Author: Judea Pearl
Publisher: John Wiley & Sons
ISBN: 1119186862
Format: PDF, Docs
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Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning.

Intuitive Biostatistics

Author: Harvey Motulsky
Publisher: Oxford University Press, USA
ISBN: 0199946647
Format: PDF, ePub, Docs
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Thoroughly revised and updated, the third edition of Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking retains and refines the core perspectives of the previous editions: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. With its engaging and conversational tone, this unique book provides a clear introduction to statistics for undergraduate and graduate students in a wide range of fields and also serves as a statistics refresher for working scientists. It is especially useful for those students in health-science related fields who have no background in biostatistics. NEW TO THIS EDITION * A new chapter on the complexities of probability * A new chapter on meta-analysis * A completely rewritten chapter on statistical traps to avoid * More sections on common mistakes in data analysis * More Q&A sections * New topics and examples * New learning tools (each chapter ends with a summary and a list of statistical terms)

The Data Science Handbook

Author: Field Cady
Publisher: John Wiley & Sons
ISBN: 1119092949
Format: PDF, ePub, Mobi
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A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Understanding Statistics in the Behavioral Sciences

Author: Robert Pagano
Publisher: Cengage Learning
ISBN: 1111837260
Format: PDF, Docs
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Based on over 30 years of successful teaching experience in this course, Robert Pagano’s introductory text takes an intuitive, concepts-based approach to descriptive and inferential statistics. He uses the sign test to introduce inferential statistics, empirically derived sampling distributions, many visual aids, and lots of interesting examples to promote student understanding. One of the hallmarks of this text is the positive feedback from students -- even students who are not mathematically inclined praise the text for its clarity, detailed presentation, and use of humor to help make concepts accessible and memorable. Thorough explanations precede the introduction of every formula, and the exercises that immediately follow include a step-by-step model that lets students compare their work against fully solved examples. This combination makes the text perfect for students taking their first statistics course in psychology or other social and behavioral sciences. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.