Teach Yourself Cluster Analysis Conjoint Analysis And Econometrics Techniques
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Teach Yourself Cluster Analysis, Conjoint Analysis, and Econometrics Techniques
This book will address such classification and econometrics techniques as cluster analysis, conjoint analysis, seemingly unrelated regression, and simultaneous equations modeling. The purpose and rationale for using each technique will be explained in lay man's terms, using illustrative concepts that are easily understood. Mathematical prerequisites are generally low; the author assumes her reader has some familiarity with descriptive statistics and multivariate analysis. After reading the book, the reader will be able to understand and apply each technique without having to know the meaning of Greek symbols and equations. The syntax and output for each technique will be discussed and the author will provide a clear explanation of how to interpret the output. Readers will know how to modify the syntax provided in the book and apply them to their own programs to use. Programming syntax in SPSS and R are provided.
Research Methods in Education
This thoroughly updated and extended eighth edition of the long-running bestseller Research Methods in Education covers the whole range of methods employed by educational research at all stages. Its five main parts cover: the context of educational research; research design; methodologies for educational research; methods of data collection; and data analysis and reporting. It continues to be the go-to text for students, academics and researchers who are undertaking, understanding and using educational research, and has been translated into several languages. It offers plentiful and rich practical advice, underpinned by clear theoretical foundations, research evidence and up-to-date references, and it raises key issues and questions for researchers planning, conducting, reporting and evaluating research. This edition contains new chapters on: Mixed methods research The role of theory in educational research Ethics in Internet research Research questions and hypotheses Internet surveys Virtual worlds, social network software and netography in educational research Using secondary data in educational research Statistical significance, effect size and statistical power Beyond mixed methods: using Qualitative Comparative Analysis (QCA) to integrate cross-case and within-case analyses. Research Methods in Education is essential reading for both the professional researcher and anyone involved in educational and social research. The book is supported by a wealth of online materials, including PowerPoint slides, useful weblinks, practice data sets, downloadable tables and figures from the book, and a virtual, interactive, self-paced training programme in research methods. These resources can be found at: www.routledge.com/cw/cohen.
Teach Yourself Cluster Analysis, Conjoint Analysis, and Econometrics Techniques
The purpose of this e-book is to make the case for the application of the classifications and econometrics techniques on issues addressed by social and behavioral scientists. This e-book will address such classification and econometrics techniques as cluster analysis, conjoint analysis, seemingly unrelated regression, and simultaneous equations modeling. Classification techniques will be discussed in length on subjects such as hierarchical agglomerative clustering, k-means clustering, and two-step clustering. Descriptive and prescriptive in nature, the e-book will start with a detailed pedagogical introduction to each of these techniques followed by a detailed description of the standards used in the application of these techniques. The author will go over the purpose and rationale for using each statistical test and provide a clear exposition of why and when each technique should be used. Each technique will be explained in lay man's terms, difficult concepts using illustrative examples that are easily understood. Mathematical prerequisite is generally low; the author assumes her reader has some familiarity with descriptive statistics and multivariate regression. After reading the e-book, the reader will be able to understand each technique and apply it to social science related research without having to know the meaning of Greek symbols and equations. In this e-book, syntax and output for each technique will be discussed and the author will provide a clear explanation of how to interpret the output. Readers will know how to modify the syntax provided in the e-book and apply them to their own programs to use. Programming syntax in SPSS and R are also provided. These syntax will help readers make sense of the results when they use SPSS software featuring cluster analysis and R software featuring conjoint analysis, seemingly unrelated regression, and simultaneously equations modeling. The purpose of the examples used in this book is to illustrate the use of various classification and econometrics techniques and should not be considered definitive.