Top 8 recommendation multiple regression and beyond
When you looking for multiple regression and beyond, you must consider not only the quality but also price and customer reviews. But among hundreds of product with different price range, choosing suitable multiple regression and beyond is not an easy task. In this post, we show you how to find the right multiple regression and beyond along with our top-rated reviews. Please check out our suggestions to find the best multiple regression and beyond for you.
When you looking for multiple regression and beyond, you must consider not only the quality but also price and customer reviews. But among hundreds of product with different price range, choosing suitable multiple regression and beyond is not an easy task. In this post, we show you how to find the right multiple regression and beyond along with our top-rated reviews. Please check out our suggestions to find the best multiple regression and beyond for you.
Best multiple regression and beyond
1. Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling
Description
Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely.
- Covers both MR and SEM, while explaining their relevance to one another
- Also includes path analysis, confirmatory factor analysis, and latent growth modeling
- Figures and tables throughout provide examples and illustrate key concepts and techniques
For additional resources, please visit: http://tzkeith.com/
2. Multiple Regression and Beyond
Description
This book is designed to provide a conceptually-oriented introduction to multiple regression. It is divided into two main parts. The author concentrates on multiple regression analysis in the first part and structural equation modeling in the second part.
- Provides an introduction to multiple regression analysis, path analysis, confirmatory factor analysis, and structural equation modeling.
- Students gain a foundation in multiple regression. Multiple regression is used as a jumping-off place for structural equation modeling with measured variables (path analysis). Latent variables are introduced as a way of obviating some of the threats to path models, and SEM with latent variables is presented as the culmination of the previous topics. (not so sure about this one)
- Conceptual, rather than formula oriented, approach
3. Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling
Description
Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely.
This book:
Covers both MR and SEM, while explaining their relevance to one another
Includes path analysis, confirmatory factor analysis, and latent growth modeling
Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises
Extensive use of figures and tables provide examples and illustrate key concepts and techniques
New to this edition:
New chapter on mediation, moderation, and common cause
New chapter on the analysis of interactions with latent variables and multilevel SEM
Expanded coverage of advanced SEM techniques in chapters 18 through 22
International case studies and examples
Updated instructor and student online resources
4. Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling 2nd edition by Keith, Timothy Z. (2014) Paperback
5. Multiple Regression and Beyond
Description
Multiple Regression and Beyond by Timothy Z Keith. Allyn & Bacon, Inc.,2006 (6. Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling by Timothy Z. Keith (2014-12-19)
7. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know
Description
Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions
Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statisticsthe art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques.
Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering lifes important questions.
Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features:
- Plentiful examples throughout aimed to strengthen readers understanding of the statistical concepts and methods
- A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression
- A case study in each chapter that illustrates the use of the presented techniques
- Highlights of well-known shortcomings that can lead to false conclusions
- An introduction to advanced techniques such as validation and bootstrapping
Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.
8. Multiple Regression and Beyond by Timothy Z. Keith (2005-07-04)