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Statistics in MATLAB: A Primer (Chapman & Hall/CRC Computer Science & Data Analysis)
by Wendy L. Martinez MoonJung ChoThis primer provides an accessible introduction to MATLAB version 8 and its extensive functionality for statistics. Fulfilling the need for a practical user's guide, the book covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB, presenting examples of how MATLAB can be used to analyze data. It explains how to determine what method should be used for analysis, and includes figures, visual aids, and access to a companion website with data sets and additional examples.
Statistics in Plain English
by Timothy C. UrdanStatistics in Plain English is a straightforward, conversational introduction to statistics that delivers exactly what its title promises. Each chapter begins with a brief overview of a statistic (or set of statistics) that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides. Chapters also include an example of the statistic (or statistics) used in real-world research, "Worked Examples," "Writing It Up" sections that demonstrate how to write about each statistic, "Wrapping Up and Looking Forward" sections, and practice work problems. Thoroughly updated throughout, this edition features several key additions and changes. First, a new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added, providing an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression). Next, the chapter on non-parametric statistics has been enhanced with in-depth descriptions of Mann-Whitney U, Kruskal-Wallis, and Wilcoxon Signed-Rank analyses, in addition to the detailed discussion of the Chi-square statistic found in the previous edition. These nonparametric statistics are widely used when dealing with nonnormally distributed data. This edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression, as well as more coverage of the normal distribution in statistics. Finally, the book features a multitude of real-world examples throughout to aid student understanding and provides them with a solid understanding of how several statistics techniques commonly used by researchers in the social sciences work. Statistics in Plain English is suitable for a wide range of readers, including students taking their first statistics course, professionals who want to refresh their statistical memory, and undergraduate or graduate students who need a concise companion to a more complicated text used in their class. The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.
Statistics in Plain English, Fourth Edition
by Timothy C. UrdanThis introductory textbook provides an inexpensive, brief overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly. Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated measures ANOVA, and factor analysis. Each chapter begins with a short description of the statistic and when it should be used. This is followed by a more in-depth explanation of how the statistic works. Finally, each chapter ends with an example of the statistic in use, and a sample of how the results of analyses using the statistic might be written up for publication. A glossary of statistical terms and symbols is also included. Using the author's own data and examples from published research and the popular media, the book is a straightforward and accessible guide to statistics. New features in the fourth edition include: sets of work problems in each chapter with detailed solutions and additional problems online to help students test their understanding of the material, new "Worked Examples" to walk students through how to calculate and interpret the statistics featured in each chapter, new examples from the author's own data and from published research and the popular media to help students see how statistics are applied and written about in professional publications, many more examples, tables, and charts to help students visualize key concepts, clarify concepts, and demonstrate how the statistics are used in the real world. a more logical flow, with correlation directly preceding regression, and a combined glossary appearing at the end of the book, a Quick Guide to Statistics, Formulas, and Degrees of Freedom at the start of the book, plainly outlining each statistic and when students should use them, greater emphasis on (and description of) effect size and confidence interval reporting, reflecting their growing importance in research across the social science disciplines an expanded website at www.routledge.com/cw/urdan with PowerPoint presentations, chapter summaries, a new test bank, interactive problems and detailed solutions to the text's work problems, SPSS datasets for practice, links to useful tools and resources, and videos showing how to calculate statistics, how to calculate and interpret the appendices, and how to understand some of the more confusing tables of output produced by SPSS. Statistics in Plain English, Fourth Edition is an ideal guide for statistics, research methods, and/or for courses that use statistics taught at the undergraduate or graduate level, or as a reference tool for anyone interested in refreshing their memory about key statistical concepts. The research examples are from psychology, education, and other social and behavioral sciences.
Statistics in Plain English, Third Edition
by Timothy C. UrdanThis inexpensive paperback provides a brief, simple overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly. Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated measures ANOVA, and factor analysis. Each chapter begins with a short description of the statistic and when it should be used. This is followed by a more in-depth explanation of how the statistic works. Finally, each chapter ends with an example of the statistic in use, and a sample of how the results of analyses using the statistic might be written up for publication. A glossary of statistical terms and symbols is also included. New features in the third edition include: a new chapter on Factor and Reliability Analysis especially helpful to those who do and/or read survey research, new "Writing it Up" sections demonstrate how to write about and interpret statistics seen in books and journals, a website at http://www.psypress.com/statistics-in-plain-english with PowerPoint presentations, interactive problems (including an overview of the problem's solution for Instructors) with an IBM SPSS dataset for practice, videos of the author demonstrating how to calculate and interpret most of the statistics in the book, links to useful websites, and an author blog, new section on understanding the distribution of data (ch. 1) to help readers understand how to use and interpret graphs, many more examples, tables, and charts to help students visualize key concepts. Statistics in Plain English, Third Edition is an ideal supplement for statistics, research methods, and/or for courses that use statistics taught at the undergraduate or graduate level, or as a reference tool for anyone interested in refreshing their memory about key statistical concepts. The research examples are from psychology, education, and other social and behavioral sciences.
Statistics in Precision Health: Theory, Methods and Applications (ICSA Book Series in Statistics)
by Ding-Geng Chen Yichuan ZhaoThis book discusses statistical methods and their innovative applications in precision health. It serves as a valuable resource to foster the development of this growing field within the context of the big data era. The chapters cover a wide range of topics, including foundational principles, statistical theories, new procedures, advanced methods, and practical applications in precision medicine. Particular attention is devoted to the interplay between precision health, big data, and mobile health research, while also exploring precision medicine's role in clinical trials, electronic health record data analysis, survival analysis, and genomic studies. Targeted at data scientists, statisticians, graduate students, and researchers in academia, industry, and government, this book offers insights into the latest advances in personalized medicine using advanced statistical techniques.
Statistics in Psychology Using R and SPSS
by Klaus Kubinger Dieter Rasch Takuya YanagidaStatistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements.The book looks at the process of empirical research into the following seven stages:Formulation of the problemStipulation of the precision requirementsSelecting the statistical model for the planning and analysisThe (optimal) design of the experiment or surveyPerforming the experiment or the surveyStatistical analysis of the observed resultsInterpretation of the results.
Statistics in Social Work: An Introduction to Practical Applications
by Professor Amy BatchelorUnderstanding statistical concepts is essential for social work professionals. It is key to understanding research and reaching evidence-based decisions in your own practice—but that is only the beginning. If you understand statistics, you can determine the best interventions for your clients. You can use new tools to monitor and evaluate the progress of your client or team. You can recognize biased systems masked by complex models and the appearance of scientific neutrality. For social workers, statistics are not just math, they are a critical practice tool.This concise and approachable introduction to statistics limits its coverage to the concepts most relevant to social workers. Statistics in Social Work guides students through concepts and procedures from descriptive statistics and correlation to hypothesis testing and inferential statistics. Besides presenting key concepts, it focuses on real-world examples that students will encounter in a social work practice. Using concrete illustrations from a variety of potential concentrations and populations, Amy Batchelor creates clear connections between theory and practice—and demonstrates the important contributions statistics can make to evidence-based and rigorous social work practice.
Statistics in the Health Sciences: Theory, Applications, and Computing (Chapman & Hall/CRC Biostatistics Series)
by Albert Vexler Alan Hutson"This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encountered in clinical trials and epidemiological studies. The authors provide a detailed discussion of methodological and applied issues in parametric, semi-parametric and nonparametric approaches, including computationally extensive data-driven techniques, such as empirical likelihood, sequential procedures, and bootstrap methods. Many of these techniques are implemented using popular software such as R and SAS."— Vlad Dragalin, Professor, Johnson and Johnson, Spring House, PA "It is always a pleasure to come across a new book that covers nearly all facets of a branch of science one thought was so broad, so diverse, and so dynamic that no single book could possibly hope to capture all of the fundamentals as well as directions of the field. The topics within the book’s purview—fundamentals of measure-theoretic probability; parametric and non-parametric statistical inference; central limit theorems; basics of martingale theory; Monte Carlo methods; sequential analysis; sequential change-point detection—are all covered with inspiring clarity and precision. The authors are also very thorough and avail themselves of the most recent scholarship. They provide a detailed account of the state of the art, and bring together results that were previously scattered across disparate disciplines. This makes the book more than just a textbook: it is a panoramic companion to the field of Biostatistics. The book is self-contained, and the concise but careful exposition of material makes it accessible to a wide audience. This is appealing to graduate students interested in getting into the field, and also to professors looking to design a course on the subject." — Aleksey S. Polunchenko, Department of Mathematical Sciences, State University of New York at Binghamton This book should be appropriate for use both as a text and as a reference. This book delivers a "ready-to-go" well-structured product to be employed in developing advanced courses. In this book the readers can find classical and new theoretical methods, open problems and new procedures. The book presents biostatistical results that are novel to the current set of books on the market and results that are even new with respect to the modern scientific literature. Several of these results can be found only in this book.
Statistics in the Public Interest: In Memory of Stephen E. Fienberg (Springer Series in the Data Sciences)
by Alicia L. Carriquiry Judith M. Tanur William F. EddyThis edited volume surveys a variety of topics in statistics and the social sciences in memory of the late Stephen Fienberg. The book collects submissions from a wide range of contemporary authors to explore the fields in which Fienberg made significant contributions, including contingency tables and log-linear models, privacy and confidentiality, forensics and the law, the decennial census and other surveys, the National Academies, Bayesian theory and methods, causal inference and causes of effects, mixed membership models, and computing and machine learning. Each section begins with an overview of Fienberg’s contributions and continues with chapters by Fienberg’s students, colleagues, and collaborators exploring recent advances and the current state of research on the topic. In addition, this volume includes a biographical introduction as well as a memorial concluding chapter comprised of entries from Stephen and Joyce Fienberg’s close friends, former students, colleagues, and other loved ones, as well as a photographic tribute.
Statistics in Toxicology Using R (Chapman And Hall/crc The R Ser.)
by Ludwig A. HothornThe apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysi
Statistics Made Easy: Flash
by Alan GrahamThe books in this bite-sized new series contain no complicated techniques or tricky materials, making them ideal for the busy, the time-pressured or the merely curious. Statistics Made Easy is a short, simple and to-the-point guide to statistics. In just 96 pages, the reader will learn all about why we do the things we do. Ideal for the busy, the time-pressured or the merely curious, Statistics Made Easy is a quick, no-effort way to break into this fascinating topic.
Statistics Made Easy: Flash
by Alan GrahamThe books in this bite-sized new series contain no complicated techniques or tricky materials, making them ideal for the busy, the time-pressured or the merely curious. Statistics Made Easy is a short, simple and to-the-point guide to statistics. In just 96 pages, the reader will learn all about why we do the things we do. Ideal for the busy, the time-pressured or the merely curious, Statistics Made Easy is a quick, no-effort way to break into this fascinating topic.
Statistics Made Simple For School Leaders: Data-Driven Decision Making
by David J. Carroll Susan Rovezzi CarrollThe chief executive officer of a corporation is not much different from a public school administrator. While CEOs base many of their decisions on data, for school administrators, this type of research may conjure up miserable memories of searching for information to meet a graduate school requirement. However, the value of data-based decision making will continue to escalate and the school community--students, teachers, parents and the general public--expect this information to come from their administrators. Administrators are called on to be accountable, but few are capable of presenting the mountain of data that they collect in a cohesive and strategic manner. Most statistical books are focused on statistical theory versus application, but Statistics Made Simple for School Leaders presents statistics in a simple, practical, conceptual, and immediately applicable manner. It enables administrators to take their data and manage it into strategic information so the results can be used for action plans that benefit the school system. The approach is "user friendly" and leaves the reader with a confident can-do attitude to communicate results and plans to staff and the community.
Statistics, New Empiricism and Society in the Era of Big Data (SpringerBriefs in Statistics)
by Giuseppe ArbiaThis book reveals the myriad aspects of Big Data collection and analysis, by defining and clarifying the meaning of Big Data and its unique characteristics in a non-technical and easy-to-follow way. Moreover, it discusses critical issues and problems related to the Big Data revolution and their implications for both Statistics as a discipline and for our everyday lives. The author identifies various problems and limitations in the quantitative analysis of Big Data, with regard to e.g. its volume, velocity and variety, as well as its reliability and veridicity. Dedicated chapters focus on the epistemological aspects of data-based knowledge and ethical aspects of the use of Big Data, while also addressing paradigmatic cases such as Cambridge Analytica and the use of data from social networks to influence election outcomes.
Statistics of Extremes
by E. J. GumbelUniversally acknowledged as the classic text about statistics of extremes, this volume is geared toward use by statisticians and statistically minded scientists and engineers. It employs elementary terms to explain applications, favors graphical procedures over calculations, and presents simple generalizations as exercises -- all of which contribute to its value for students. Starting with definitions of its aims and tools, the text proceeds to discussions of order statistics and their exceedances, exact distribution of extremes, and analytical study of extremes. Additional topics include the first asymptotic distribution; uses of the first, second, and third asymptotes; and the range. 1958 edition. 44 tables. 97 graphs.
Statistics of Financial Markets: An Introduction (Universitext)
by Jürgen Franke Wolfgang Karl Härdle Christian Matthias HafnerNow in its fifth edition, this book offers a detailed yet concise introduction to the growing field of statistical applications in finance. The reader will learn the basic methods for evaluating option contracts, analyzing financial time series, selecting portfolios and managing risks based on realistic assumptions about market behavior. The focus is both on the fundamentals of mathematical finance and financial time series analysis, and on applications to specific problems concerning financial markets, thus making the book the ideal basis for lectures, seminars and crash courses on the topic. All numerical calculations are transparent and reproducible using quantlets.For this new edition the book has been updated and extensively revised and now includes several new aspects such as neural networks, deep learning, and crypto-currencies. Both R and Matlab code, together with the data, can be downloaded from the book’s product page and the Quantlet platform.The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allow readers to reproduce the tables, pictures and calculations inside this Springer book.“This book provides an excellent introduction to the tools from probability and statistics necessary to analyze financial data. Clearly written and accessible, it will be very useful to students and practitioners alike.”Yacine Ait-Sahalia, Otto Hack 1903 Professor of Finance and Economics, Princeton University
Statistics of Financial Markets: Exercises and Solutions
by Brenda López-Cabrera Wolfgang Karl Härdle Szymon BorakPractice makes perfect. Therefore the best method of mastering models is working with them. This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123. The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges.
Statistics of Medical Imaging (Chapman & Hall/CRC Interdisciplinary Statistics)
by Tianhu LeiStatistical investigation into technology not only provides a better understanding of the intrinsic features of the technology (analysis), but also leads to an improved design of the technology (synthesis). Physical principles and mathematical procedures of medical imaging technologies have been extensively studied during past decades. However, les
Statistics on the Table: The History of Statistical Concepts and Methods
by Stephen M. StiglerThis lively collection of essays examines in witty detail the history of some of the concepts involved in bringing statistical argument "to the table," and some of the pitfalls that have been encountered. The topics range from seventeenth-century medicine and the circulation of blood, to the cause of the Great Depression and the effect of the California gold discoveries of 1848 upon price levels, to the determinations of the shape of the Earth and the speed of light, to the meter of Virgil's poetry and the prediction of the Second Coming of Christ. The title essay tells how the statistician Karl Pearson came to issue the challenge to put "statistics on the table" to the economists Marshall, Keynes, and Pigou in 1911. The 1911 dispute involved the effect of parental alcoholism upon children, but the challenge is general and timeless: important arguments require evidence, and quantitative evidence requires statistical evaluation. Some essays examine deep and subtle statistical ideas such as the aggregation and regression paradoxes; others tell of the origin of the Average Man and the evaluation of fingerprints as a forerunner of the use of DNA in forensic science. Several of the essays are entirely nontechnical; all examine statistical ideas with an ironic eye for their essence and what their history can tell us about current disputes.
Statistics Super Review
by Statistics Study GuidesGet all you need to know with Super Reviews! Each Super Review is packed with in-depth, student-friendly topic reviews that fully explain everything about the subject. The Statistics Super Review includes frequency distributions, numerical methods of describing data, measures of variability, probability, distributions, sampling theory, statistical inference, general linear model inferences, experimental design, the chi-square test, and time series. Take the Super Review quizzes to see how much you've learned - and where you need more study. Makes an excellent study aid and textbook companion. Great for self-study! DETAILS - From cover to cover, each in-depth topic review is easy-to-follow and easy-to-grasp - Perfect when preparing for homework, quizzes, and exams! - Review questions after each topic that highlight and reinforce key areas and concepts - Student-friendly language for easy reading and comprehension - Includes quizzes that test your understanding of the subject
Statistics Super Review, 2nd Ed.
by The Editors of REANeed help with Statistics? Want a quick review or refresher for class? This is the book for you! REA's Statistics Super Review gives you everything you need to know!This Super Review can be used as a supplement to your high school or college textbook, or as a handy guide for anyone who needs a fast review of the subject.* Comprehensive, yet concise coverage - review covers the material that students must know about statistics. Each topic is presented in a clear and easy-to-understand format that makes learning easier.* Questions and answers for each topic - let you practice what you've learned and build your statistics skills.* End-of-chapter quizzes - gauge your understanding of the important information you need to know, so you'll be ready for any homework assignment, quiz, or test.Whether you need a quick refresher on the subject, or are prepping for your next exam, we think you'll agree that REA's Super Review provides all you need to know!
Statistics Tables: For Mathematicians, Engineers, Economists and the Behavioural and Management Sciences
by Henry R. NeaveFor three decades, Henry Neave’s Statistics Tables has been the gold standard for all students taking an introductory statistical methods course as part of their wider degree in a host of disciplines including mathematics, economics, business and management, geography and psychology. The period has seen a large increase in the level of mathematics and statistics required to achieve these qualifications and Statistics Tables has helped several generations of students meet their goals. All the features of the first edition are retained including the full range of best-known standard statistical techniques, as well as some lesser-known methods that can be hard to track down elsewhere. The explanatory introductions to each section have been updated and the second edition benefits from the inclusion of a valuable and comprehensive new section on an approach to simple but powerful investigation of process data. This will help the book continue in its position as the prime statistical reference for all students of mathematics, engineering and the social sciences, and everyone who needs effective methods for analysing data.
Statistics, Testing, and Defense Acquisition: New Approaches and Methodological Improvements
by Panel on Statistical Methods for Testing Evaluating Defense SystemsFor every weapons system being developed, the U.S. Department of Defense (DOD) must make a critical decision: Should the system go forward to full-scale production? The answer to that question may involve not only tens of billions of dollars but also the nation's security and military capabilities. In the milestone process used by DOD to answer the basic acquisition question, one component near the end of the process is operational testing, to determine if a system meets the requirements for effectiveness and suitability in realistic battlefield settings. Problems discovered at this stage can cause significant production delays and can necessitate costly system redesign.This book examines the milestone process, as well as the DOD's entire approach to testing and evaluating defense systems. It brings to the topic of defense acquisition the application of scientific statistical principles and practices.
Statistics Through Applications
by Daren S. Starnes Daniel S. Yates David S. MooreWatch avideo introduction here. Statistics Through Applications (STA)is the only text written specifically for high school statistics course. Designed to be read, the book takes a data analysis approach that emphasizes conceptual understanding over computation, while recognizing that some computation is necessary. The focus is on the statistical thinking behind data gathering and interpretation. The high school statistics course is often the first applied math course students take. STAengages students in learning how statisticians contribute to our understanding of the world and helps students to become more discerning consumers of the statistics they encounter in ads, economic reports, political campaigns, and elsewhere. New and improved!STA 2efeatures expanded coverage of probability, a reorganized presentation of data analysis, a new color design and much more. Please see theposted sample chapter orrequest a copy today to see for yourself.
Statistics Through Applications
by Daniel Yates Daren S. Starnes David MooreStatistics Through Applications (STA) is the only text written specifically for high school statistics course. Designed to be read, the book takes a data analysis approach that emphasizes conceptual understanding over computation, while recognizing that some computation is necessary. The focus is on the statistical thinking behind data gathering and interpretation. The high school statistics course is often the first applied math course students take. STA engages students in learning how statisticians contribute to our understanding of the world and helps students to become more discerning consumers of the statistics they encounter in ads, economic reports, political campaigns, and elsewhere. New and improved! STA 2e features expanded coverage of probability, a reorganized presentation of data analysis, a new color design and much more.