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Applied Univariate Bivariate And Multivariate Statistics

Author: Daniel J. Denis
Publisher: John Wiley & Sons
ISBN: 1118632338
Size: 75.99 MB
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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.--

Spss Data Analysis For Univariate Bivariate And Multivariate Statistics

Author: Daniel J. Denis
Publisher: John Wiley & Sons
ISBN: 111946580X
Size: 43.72 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 Multivariate Statistics With R

Author: Daniel Zelterman
Publisher: Springer
ISBN: 3319140930
Size: 23.22 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 Statistics From Bivariate Through Multivariate Techniques

Author: Rebecca M. Warner
Publisher: SAGE
ISBN: 141299134X
Size: 59.68 MB
Format: PDF, Kindle
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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 Multivariate Statistical Concepts

Author: Debbie L. Hahs-Vaughn
Publisher: Taylor & Francis
ISBN: 1317811372
Size: 50.30 MB
Format: PDF, Kindle
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More comprehensive than other texts, this new book covers the classic and cutting edge multivariate techniques used in today’s research. Ideal for courses on multivariate statistics/analysis/design, advanced statistics or quantitative techniques taught in psychology, education, sociology, and business, the book also appeals to researchers with no training in multivariate methods. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps reader’s master key concepts so they can implement and interpret results generated by today’s sophisticated software. Annotated screenshots from SPSS and other packages are integrated throughout. Designed for course flexibility, after the first 4 chapters, instructors can use chapters in any sequence or combination to fit the needs of their students. Each chapter includes a ‘mathematical snapshot’ that highlights the technical components of each procedure, so only the most crucial equations are included. Highlights include: -Outlines, key concepts, and vignettes related to key concepts preview what’s to come in each chapter -Examples using real data from education, psychology, and other social sciences illustrate key concepts -Extensive coverage of assumptions including tables, the effects of their violation, and how to test for each technique -Conceptual, computational, and interpretative problems mirror the real-world problems students encounter in their studies and careers -A focus on data screening and power analysis with attention on the special needs of each particular method -Instructions for using SPSS via screenshots and annotated output along with HLM, Mplus, LISREL, and G*Power where appropriate, to demonstrate how to interpret results -Templates for writing research questions and APA-style write-ups of results which serve as models -Propensity score analysis chapter that demonstrates the use of this increasingly popular technique -A review of matrix algebra for those who want an introduction (prerequisites include an introduction to factorial ANOVA, ANCOVA, and simple linear regression, but knowledge of matrix algebra is not assumed) -www.routledge.com/9780415842365 provides the text’s datasets preformatted for use in SPSS and other statistical packages for readers, as well as answers to all chapter problems, Power Points, and test items for instructors

Applied Multivariate Statistical Analysis

Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
ISBN: 9783540030799
Size: 64.36 MB
Format: PDF, Kindle
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These are the exciting memoirs of an articulate black lady, who survived the destitution of her childhood by scavenging in the Mobile, Alabama, city dump. She lived in the segregated South during the era of Civil Rights demonstrations. As a mother of six, she overcame the shock of discovering she was one of several wives with whom her itinerant preacher husband claimed conjugal privileges. She became an artist's model in Boston, where she experienced racist terror and love of a white man. This is a beautiful, upbeat book of love, happiness and the survival of the spirit.

Applied Multivariate Research

Author: Lawrence S. Meyers
Publisher: SAGE
ISBN: 141298811X
Size: 53.36 MB
Format: PDF, ePub, Docs
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This book provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter, using a conceptual, non-mathematical, approach. Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path analysis, and structural equation modeling, it is geared toward the needs, level of sophistication, and interest in multivariate methodology that serves students in applied programs in the social and behavioral sciences. Readers are encouraged to focus on design and interpretation rather than the intricacies of specific computations.

Methods Of Multivariate Analysis Basic Applications

Author: Alvin C. Rencher
Publisher: Wiley-Interscience
ISBN:
Size: 56.64 MB
Format: PDF, Docs
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Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. "Methods of Multivariate Analysis" provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.