applied univariate bivariate and multivariate statistics using r

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Applied Multivariate Statistics With R

Author : Daniel Zelterman
ISBN : 9783319140933
Genre : Medical
File Size : 88. 3 MB
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This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary.

Applied Univariate Bivariate And Multivariate Statistics

Author : Daniel J. Denis
ISBN : 9781118632239
Genre : Mathematics
File Size : 76. 17 MB
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A clear and efficient balance between theory and application of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction, Applied Univariate, Bivariate, and Multivariate Statistics provides an overview of statistical modeling techniques used in fields in the social and behavioral sciences. Blending statistical theory and methodology, the book surveys both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques such as t-tests and correlation as well as more advanced procedures such as MANOVA, factor analysis, and structural equation modeling. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. Applied Univariate, Bivariate, and Multivariate Statistics also features Demonstrations of statistical techniques using software packages such as R and SPSS® Examples of hypothetical and real data with subsequent statistical analyses Historical and philosophical insights into many of the techniques used in modern social science A companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options An ideal textbook for courses in statistics and methodology at the upper- undergraduate and graduate-levels in psychology, political science, biology, sociology, education, economics, communications, law, and survey research, Applied Univariate, Bivariate, and Multivariate Statistics is also a useful reference for practitioners and researchers in their field of application. DANIEL J. DENIS, PhD, is Associate Professor of Quantitative Psychology at the University of Montana where he teaches courses in univariate and multivariate statistics. He has published a number of articles in peer-reviewed journals and has served as consultant to researchers and practitioners in a variety of fields.

Spss Data Analysis For Univariate Bivariate And Multivariate Statistics

Author : Daniel J. Denis
ISBN : 9781119465782
Genre : Mathematics
File Size : 70. 36 MB
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Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.

Applied Statistics From Bivariate Through Multivariate Techniques

Author : Rebecca M. Warner
ISBN : 9781412991346
Genre : Mathematics
File Size : 59. 42 MB
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Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.

Applied Stochastic Hydrogeology

Author : Yoram Rubin
ISBN : 0198031548
Genre : Science
File Size : 89. 87 MB
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Stochastic Subsurface Hydrogeology is the study of subsurface, geological heterogeneity, and its effects on flow and transport process, using probabilistic and geostatistical concepts. This book presents a rational, systematic approach for analyzing and modeling subsurface heterogeneity, and for modeling flow and transport in the subsurface, and for prediction and decision-making under uncertainty. The book covers the fundamentals and practical aspects of geostatistics and stochastic hydrogeology, coupling theoretical and practical aspects, with examples, case studies and guidelines for applications, and provides a summary and review of the major developments in these areas.

Applied Probabilistic Calculus For Financial Engineering

Author : Bertram K. C. Chan
ISBN : 9781119387619
Genre : Business & Economics
File Size : 44. 31 MB
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Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a "Random Walk" Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R is an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.

Applied Social Research

Author : Duane R. Monette
ISBN : NWU:35556036605566
Genre : Social Science
File Size : 78. 36 MB
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Presenting the methods of social science research within the context of human service practice, the Fifth Edition of APPLIED SOCIAL RESEARCH is ideal for courses emphasizing applied research in human services, sociology, social work, criminal justice, counseling, and community planning. In this revised edition, the authors show research and human service practice as allies bound by common goals of advancing knowledge and creating a better world. Covering the full range of topics included in traditional social science research methods courses, the book devotes considerable attention to both qualitative and quantitative research methods. Used at the undergraduate and graduate levels, this popular text explores the growing diversity of ways in which research is applied to practice and the extensive links between research and practice.

Multivariate Statistical Quality Control Using R

Author : Edgar Santos-Fernández
ISBN : 9781461454526
Genre : Computers
File Size : 41. 40 MB
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​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

Research Methods For Massage And Holistic Therapies E Book

Author : Glenn Hymel
ISBN : 9780323070492
Genre : Medical
File Size : 55. 11 MB
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This comprehensive resource covers a broad array of research strategies available to massage therapists to give them the tools they need to be knowledgeable readers of research literature, as well as active researchers. The primary focus of the book is on the quantitative aspect of research that encompasses the principal types of studies most extensively used in the various health care professions, specifically massage therapy. Extensive coverage is also given to the qualitative and integrative research categories that are progressively gaining recognition among researchers in various health science disciplines and professions. Accommodates the March 2003 mandate from the Commission on Massage Therapy Accreditation (COMTA) that massage therapy schools incorporate into their curricula provisions to ensure a research literate profession. Examples and techniques for interpreting research guide practitioners and students to be knowledgeable readers of massage therapy research, allowing application to practice. Relies heavily on concept maps, flowcharts, tables, and illustrations and excerpts of published studies to augment the book's narrative development of topics by providing pictorial displays and summaries of the material. Literature-based and hypothetical research examples/illustrations from several manual therapy professions employing therapeutic massage make the material pertinent to real-life settings An introductory section at the beginning of each chapter reviews the material covered in the previous chapter and how it relates to the new material. Chapter coverage spans the quantitative, qualitative, and integrative research categories and affiliated research strategies and methods are considered in detail. Review/summary tables give an overview of the narrative development of topics. Boxes provide the essential features of a given topic. Relies on multiple examples of possible research scenarios and illustrative excerpts from the published research literature. Content is cross-referenced for use with the Massage Therapy Foundation's Massage Therapy Research Curriculum Kit to provide both instructors and students in the 6-, 15-, and 24-hour options/levels an extensively-developed resource in one place. Each chapter includes recommended web sites and software application packages for further information.

Applied Multivariate Analysis

Author : Neil H. Timm
ISBN : 9780387227719
Genre : Mathematics
File Size : 85. 1 MB
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This book provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0.

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