Download or read book Understanding Correlation Matrices written by Alexandria R. Hadd and published by Quantitative Applications in t. This book was released on 2021-01-05 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Correlation matrices (along with their unstandardized counterparts, covariance matrices) underlie much of the statistical machinery in common use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one coefficient in the matrix puts constraints on the values of the others, and this is a major theme of the volume. In Understanding Correlation Matrices authors Alexandria Hadd and Joseph Lee Rodgers illustrate their key points with a wide range of lively examples, including correlations between intelligence measured at different ages through adolescence; correlations between public health expenditures, health life expectancy, adult mortality, and other country characteristics; correlations between wellbeing and state-level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course.
Download or read book Understanding Correlation Matrices written by Alexandria Hadd and published by SAGE Publications. This book was released on 2020-11-29 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Correlation matrices (along with their unstandardized counterparts, covariance matrices) underlie the majority the statistical methods that researchers use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one correlation in the matrix puts constraints on the values of the others, and the multivariate implications of this statement is a major theme of the volume. Alexandria Hadd and Joseph Lee Rodgers cover many features of correlations matrices including statistical hypothesis tests, their role in factor analysis and structural equation modeling, and graphical approaches. They illustrate the discussion with a wide range of lively examples including correlations between intelligence measured at different ages through adolescence; correlations between country characteristics such as public health expenditures, health life expectancy, and adult mortality; correlations between well-being and state-level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course. This volume may be used effectively across a number of disciplines in both undergraduate and graduate statistics classrooms, and also in the research laboratory.
Download or read book R Graphics Cookbook written by Winston Chang and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Practical recipes for visualizing data"--Cover.
Download or read book The Princeton Companion to Mathematics written by Timothy Gowers and published by Princeton University Press. This book was released on 2010-07-18 with total page 1057 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ultimate mathematics reference book This is a one-of-a-kind reference for anyone with a serious interest in mathematics. Edited by Timothy Gowers, a recipient of the Fields Medal, it presents nearly two hundred entries—written especially for this book by some of the world's leading mathematicians—that introduce basic mathematical tools and vocabulary; trace the development of modern mathematics; explain essential terms and concepts; examine core ideas in major areas of mathematics; describe the achievements of scores of famous mathematicians; explore the impact of mathematics on other disciplines such as biology, finance, and music—and much, much more. Unparalleled in its depth of coverage, The Princeton Companion to Mathematics surveys the most active and exciting branches of pure mathematics. Accessible in style, this is an indispensable resource for undergraduate and graduate students in mathematics as well as for researchers and scholars seeking to understand areas outside their specialties. Features nearly 200 entries, organized thematically and written by an international team of distinguished contributors Presents major ideas and branches of pure mathematics in a clear, accessible style Defines and explains important mathematical concepts, methods, theorems, and open problems Introduces the language of mathematics and the goals of mathematical research Covers number theory, algebra, analysis, geometry, logic, probability, and more Traces the history and development of modern mathematics Profiles more than ninety-five mathematicians who influenced those working today Explores the influence of mathematics on other disciplines Includes bibliographies, cross-references, and a comprehensive index Contributors include: Graham Allan, Noga Alon, George Andrews, Tom Archibald, Sir Michael Atiyah, David Aubin, Joan Bagaria, Keith Ball, June Barrow-Green, Alan Beardon, David D. Ben-Zvi, Vitaly Bergelson, Nicholas Bingham, Béla Bollobás, Henk Bos, Bodil Branner, Martin R. Bridson, John P. Burgess, Kevin Buzzard, Peter J. Cameron, Jean-Luc Chabert, Eugenia Cheng, Clifford C. Cocks, Alain Connes, Leo Corry, Wolfgang Coy, Tony Crilly, Serafina Cuomo, Mihalis Dafermos, Partha Dasgupta, Ingrid Daubechies, Joseph W. Dauben, John W. Dawson Jr., Francois de Gandt, Persi Diaconis, Jordan S. Ellenberg, Lawrence C. Evans, Florence Fasanelli, Anita Burdman Feferman, Solomon Feferman, Charles Fefferman, Della Fenster, José Ferreirós, David Fisher, Terry Gannon, A. Gardiner, Charles C. Gillispie, Oded Goldreich, Catherine Goldstein, Fernando Q. Gouvêa, Timothy Gowers, Andrew Granville, Ivor Grattan-Guinness, Jeremy Gray, Ben Green, Ian Grojnowski, Niccolò Guicciardini, Michael Harris, Ulf Hashagen, Nigel Higson, Andrew Hodges, F. E. A. Johnson, Mark Joshi, Kiran S. Kedlaya, Frank Kelly, Sergiu Klainerman, Jon Kleinberg, Israel Kleiner, Jacek Klinowski, Eberhard Knobloch, János Kollár, T. W. Körner, Michael Krivelevich, Peter D. Lax, Imre Leader, Jean-François Le Gall, W. B. R. Lickorish, Martin W. Liebeck, Jesper Lützen, Des MacHale, Alan L. Mackay, Shahn Majid, Lech Maligranda, David Marker, Jean Mawhin, Barry Mazur, Dusa McDuff, Colin McLarty, Bojan Mohar, Peter M. Neumann, Catherine Nolan, James Norris, Brian Osserman, Richard S. Palais, Marco Panza, Karen Hunger Parshall, Gabriel P. Paternain, Jeanne Peiffer, Carl Pomerance, Helmut Pulte, Bruce Reed, Michael C. Reed, Adrian Rice, Eleanor Robson, Igor Rodnianski, John Roe, Mark Ronan, Edward Sandifer, Tilman Sauer, Norbert Schappacher, Andrzej Schinzel, Erhard Scholz, Reinhard Siegmund-Schultze, Gordon Slade, David J. Spiegelhalter, Jacqueline Stedall, Arild Stubhaug, Madhu Sudan, Terence Tao, Jamie Tappenden, C. H. Taubes, Rüdiger Thiele, Burt Totaro, Lloyd N. Trefethen, Dirk van Dalen, Richard Weber, Dominic Welsh, Avi Wigderson, Herbert Wilf, David Wilkins, B. Yandell, Eric Zaslow, and Doron Zeilberger
Download or read book Logistic Regression written by Fred C. Pampel and published by SAGE. This book was released on 2000-05-26 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trying to determine when to use a logistic regression and how to interpret the coefficients? Frustrated by the technical writing in other books on the topic? Pampel's book offers readers the first "nuts and bolts" approach to doing logist
Download or read book Exploratory Factor Analysis written by W. Holmes Finch and published by SAGE Publications. This book was released on 2019-09-05 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data. It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.
Download or read book More Than Meets the Eye written by Arthur G. Bedeian and published by . This book was released on 2015 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author of this essay wonders whether in teaching our students the latest analytic techniques we have neglected to emphasize the importance of understanding the most basic aspects of a study's primary data. In response, he provides a 12-part answer to a fundamental question: “what information can be derived from reviewing the descriptive statistics and correlation matrix that appear in virtually every empirically based, nonexperimental paper published in the management discipline?” The seeming ubiquity of strained responses, to what many at first consider to be a vexed question about a mundane topic, leads the author to suggest that students at all levels, seasoned scholars, manuscript referees, and general consumers of management research may be unaware that the standard table 1 in a traditional results section reveals “more than meets the eye!”
Download or read book Robust Technology with Analysis of Interference in Signal Processing written by T. A. Aliev and published by Springer Science & Business Media. This book was released on 2003-01-31 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aliev (cybernetics, National Academy of Sciences of Azerbaijan) explores the possibility that the hidden microchanges revealed by interference estimates may be used to predict failures of various objects. The monograph discusses analysis of noise as a carrier of information forming the basis for the robust technology of noisy signals processing which has applications for control, identification, diagnostics, and pattern recognition in fields including petrochemistry, aviation, medicine, and physics. The monograph may be of interest to students, engineers, and scientists concerned with processing measurement information on computers. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).
Download or read book Data Analysis with IBM SPSS Statistics written by Kenneth Stehlik-Barry and published by Packt Publishing Ltd. This book was released on 2017-09-22 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master data management & analysis techniques with IBM SPSS Statistics 24 About This Book Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data Choose the right statistical technique to analyze different types of data and build efficient models from your data with ease Overcome any hurdle that you might come across while learning the different SPSS Statistics concepts with clear instructions, tips and tricks Who This Book Is For This book is designed for analysts and researchers who need to work with data to discover meaningful patterns but do not have the time (or inclination) to become programmers. We assume a foundational understanding of statistics such as one would learn in a basic course or two on statistical techniques and methods. What You Will Learn Install and set up SPSS to create a working environment for analytics Techniques for exploring data visually and statistically, assessing data quality and addressing issues related to missing data How to import different kinds of data and work with it Organize data for analytical purposes (create new data elements, sampling, weighting, subsetting, and restructure your data) Discover basic relationships among data elements (bivariate data patterns, differences in means, correlations) Explore multivariate relationships Leverage the offerings to draw accurate insights from your research, and benefit your decision-making In Detail SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease. Style and approach Provides a practical orientation to understanding a set of data and examining the key relationships among the data elements. Shows useful visualizations to enhance understanding and interpretation. Outlines a roadmap that focuses the process so decision regarding how to proceed can be made easily.
Download or read book Meta Analysis written by Mike W.-L. Cheung and published by John Wiley & Sons. This book was released on 2015-05-06 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.
Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE Publications. This book was released on 2021-01-11 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
Download or read book Handbook of Meta Analysis written by Christopher H. Schmid and published by CRC Press. This book was released on 2020-09-07 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Provides a comprehensive overview of meta-analysis methods and applications. 2. Divided into four major sub-topics, covering univariate meta-analysis, multivariate, applications and policy. 3. Designed to be suitable for graduate students and researchers new to the field. 4. Includes lots of real examples, with data and software code made available. 5. Chapters written by the leading researchers in the field.
Download or read book Multilevel Structural Equation Modeling written by Bruno Castanho Silva and published by SAGE Publications. This book was released on 2019-02-28 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Download or read book Basics of Matrix Algebra for Statistics with R written by Nick Fieller and published by CRC Press. This book was released on 2018-09-03 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Thorough Guide to Elementary Matrix Algebra and Implementation in R Basics of Matrix Algebra for Statistics with R provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The book introduces the definition of a matrix and the basic rules of addition, subtraction, multiplication, and inversion. Later topics include determinants, calculation of eigenvectors and eigenvalues, and differentiation of linear and quadratic forms with respect to vectors. The text explores how these concepts arise in statistical techniques, including principal component analysis, canonical correlation analysis, and linear modeling. In addition to the algebraic manipulation of matrices, the book presents numerical examples that illustrate how to perform calculations by hand and using R. Many theoretical and numerical exercises of varying levels of difficulty aid readers in assessing their knowledge of the material. Outline solutions at the back of the book enable readers to verify the techniques required and obtain numerical answers. Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It prepares readers for higher-level and specialized studies in statistics.
Download or read book Fighting Churn with Data written by Carl Gold and published by Simon and Schuster. This book was released on 2020-11-13 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. Summary The beating heart of any product or service business is returning clients. Don't let your hard-won customers vanish, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Keeping customers active and engaged is essential for any business that relies on recurring revenue and repeat sales. Customer turnover—or “churn”—is costly, frustrating, and preventable. By applying the techniques in this book, you can identify the warning signs of churn and learn to catch customers before they leave. About the book Fighting Churn with Data teaches developers and data scientists proven techniques for stopping churn before it happens. Packed with real-world use cases and examples, this book teaches you to convert raw data into measurable behavior metrics, calculate customer lifetime value, and improve churn forecasting with demographic data. By following Zuora Chief Data Scientist Carl Gold’s methods, you’ll reap the benefits of high customer retention. What's inside Calculating churn metrics Identifying user behavior that predicts churn Using churn reduction tactics with customer segmentation Applying churn analysis techniques to other business areas Using AI for accurate churn forecasting About the reader For readers with basic data analysis skills, including Python and SQL. About the author Carl Gold (PhD) is the Chief Data Scientist at Zuora, Inc., the industry-leading subscription management platform. Table of Contents: PART 1 - BUILDING YOUR ARSENAL 1 The world of churn 2 Measuring churn 3 Measuring customers 4 Observing renewal and churn PART 2 - WAGING THE WAR 5 Understanding churn and behavior with metrics 6 Relationships between customer behaviors 7 Segmenting customers with advanced metrics PART 3 - SPECIAL WEAPONS AND TACTICS 8 Forecasting churn 9 Forecast accuracy and machine learning 10 Churn demographics and firmographics 11 Leading the fight against churn
Download or read book Introduction to Time Series Analysis written by Mark Pickup and published by SAGE Publications. This book was released on 2014-10-15 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University
Download or read book A Step by Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling written by Larry Hatcher and published by SAS Institute. This book was released on 2013-03-01 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all userseven those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.
