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.

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.

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.

Building Intelligent Enterprises by leveraging the emerging and next-generation technologies to accelerate the adoption of digital transformation The speed of innovation and emerging IT technologies are changing at a very fast pace and enterprises are eager to join the digital revolution so they can stand above the competition and succeed as the enterprise of tomorrow. This book is an attempt to make the enterprise intelligent by providing the path to digital transformation and the adoption of new IT methods, tools and technologies. This book has been organized to cover the following topics: Digital Transformation, Design Thinking, Agile, DevOps, Robotic Process Automation, Internet of Things, Artificial Intelligence, Machine Learning, Blockchain, Drones, Augmented and Virtual Reality, 3D Printing, Big Data, Analytics, Cloud Computing, APIs, and SAP Leonardo. No prior knowledge of any technical coding or language is necessary to understand the content of this book. End-to-end storyline to accelerate the enterprise’s digital transformation journey How an enterprise can stay relevant, compete, and perform in the digital economy How to leverage these technologies to build intelligent enterprises Understand and apply the emerging technologies across key business processes Industry-specific Use Cases for all technologies as a reference point to build the business case for implementation The book is very well suited towards the C-Suite executives, both IT and business leaders, directors and managers, project managers, solution architects, and all professionals who have an interest and desire to keep up-to-date with the latest technological trends, looking for a career change, want to help enterprise adapt and onboard the digital roadmap, or have an agenda to digitize key processes within the enterprise to make it intelligent.

Marketing Research and Modeling addresses state of the art developments including new techniques and methodologies by leading experts in marketing and marketing research. This work emphasizes new developments in Bayesian Decision Analysis, Multivariate Analysis, Multidimensional Scaling, Conjoint Analysis, Applications of Conjoint and MDS technique, Data Mining, Cluster Analysis, and Neural Networks.

This volume introduces the theory, method, and applications of one type of conjoint analysis technique. These techniques are used to study individual judgement and decision processes and forecast the chosen behavior of individuals or the populations they represent.

Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on: confirmatory factor analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-group confirmatory factor analysis and analysis of covariance structures. Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software.

Marketing Science contributes significantly to the development and validation of analytical tools with a wide range of applications in business, public policy and litigation support. The Handbook of Marketing Analytics showcases the analytical methods used in marketing and their high-impact real-life applications. Fourteen chapters provide an overview of specific marketing analytic methods in some technical detail and 22 case studies present thorough examples of the use of each method in marketing management, public policy, and litigation support. All contributing authors are recognized authorities in their area of specialty.

How statistical thinking and methodology can help you make crucial business decisions Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance. Explores why statistical thinking is necessary and helpful Provides case studies that illustrate how to integrate several statistical tools into the decision-making process Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems With an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.

The Handbook of Marketing Research comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm.