Multivariate Data Analysis

Author: Joseph Hair
Publisher: Pearson Higher Ed
ISBN: 0133792684
Format: PDF, Kindle
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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.

Multivariate Data Analysis Pearson New International Edition

Author: Joseph F. Hair
Publisher: Pearson Higher Ed
ISBN: 1292035110
Format: PDF, ePub, Docs
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For graduate and upper-level undergraduate marketing research courses. For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this seventh revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.

Multivariate Data Analysis

Author: Joseph F. Hair (Jr)
Publisher:
ISBN: 9781292021904
Format: PDF, Mobi
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Offering an applications-oriented approach which focuses on the use of each technique rather than its mathematical derivation, this textbook introduces a six-step framework for organising and discussing multivariate data analysis techniques.

Using Multivariate Statistics

Author: Barbara G. Tabachnick
Publisher:
ISBN: 9780134790541
Format: PDF, Kindle
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For advanced undergraduate and graduate courses in Social Statistics. An in-depth introduction to today's most commonly used statistical and multivariate techniques Using Multivariate Statistics, 7th Edition presents complex statistical procedures in a way that is maximally useful and accessible to researchers who may not be statisticians. The authors focus on the benefits and limitations of applying a technique to a data set - when, why, and how to do it. Only a limited knowledge of higher-level mathematics is assumed. Students using this text will learn to conduct numerous types of multivariate statistical analyses; find the best technique to use; understand limitations to applications; and learn how to use SPSS and SAS syntax and output. 0134790545 / 9780134790541 Using Multivariate Statistics, 7/e

A Primer on Partial Least Squares Structural Equation Modeling PLS SEM

Author: Joseph F. Hair, Jr.
Publisher: SAGE Publications
ISBN: 1483377466
Format: PDF, ePub, Mobi
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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt is a practical guide that provides concise instructions on how to use partial least squares structural equation modeling (PLS-SEM), an evolving statistical technique, to conduct research and obtain solutions. Featuring the latest research, new examples using the SmartPLS software, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

An Introduction to Statistical Methods and Data Analysis

Author: R. Lyman Ott
Publisher: Cengage Learning
ISBN: 1111779988
Format: PDF, Mobi
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Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and in news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Advanced Issues in Partial Least Squares Structural Equation Modeling

Author: Joseph F. Hair, Jr.
Publisher: SAGE Publications
ISBN: 1483377415
Format: PDF, ePub, Docs
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Written as an extension of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Second Edition, this easy-to-understand, practical guide covers advanced content on PLS-SEM to help students and researchers apply techniques to research problems and accurately interpret results. Authors Joseph F. Hair, Jr., Marko Sarstedt, Christian Ringle, and Siegfried P. Gudergan provide a brief overview of basic concepts before moving to the more advanced material. Offering extensive examples on SmartPLS 3 software and accompanied by free downloadable data sets, the book emphasizes that any advanced PLS-SEM approach should be carefully applied to ensure that it fits the appropriate research context and the data characteristics that underpin the research.

Performing Data Analysis Using IBM SPSS

Author: Lawrence S. Meyers
Publisher: John Wiley & Sons
ISBN: 1118357019
Format: PDF, ePub
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Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis.

An Introduction to Statistical Methods and Data Analysis

Author: R. Lyman Ott
Publisher: Cengage Learning
ISBN: 1305465520
Format: PDF, Mobi
Download Now
Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Seventh Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Theory Based Data Analysis for the Social Sciences

Author: Carol S. Aneshensel
Publisher: SAGE
ISBN: 1412994357
Format: PDF, ePub, Mobi
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This book presents a method for bringing data analysis and statistical technique into line with theory. The author begins by describing the elaboration model for analyzing the empirical association between variables. She then introduces a new concept into this model, the focal relationship. Building upon the focal relationship as the cornerstone for all subsequent analysis, two analytic strategies are developed to establish its internal validity: an exclusionary strategy to eliminate alternative explanations, and an inclusive strategy which looks at the interconnected set of relationships predicted by theory. Using real examples of social research, the author demonstrates the use of this approach for two common forms of analysis, multiple linear regression and logistic regression. Whether learning data analysis for the first time or adding new techniques to your repertoire, this book provides an excellent basis for theory-based data analysis.