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Quantitative Data Analysis

A Companion for Accounting and Information Systems Research

This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in.

This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions.

Exploratory Data Analysis in Empirical Research

Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Munich, March 14–16, 2001

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis.

An Introduction to Statistics and Data Analysis Using Stata®

From Research Design to Final Report

An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

Introduction to Research Methods and Data Analysis in Psychology

This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods. Highly practical in nature, the book guides you, step-by-step, through the research process and is underpinned by SPSS screenshots, diagrams and examples throughout.

This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods.

Research Design and Statistical Analysis

Third Edition

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book’s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them. Changes in the New Edition: Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed. A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations. A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study. A new chapter (27) on common errors in data analysis and interpretation. Increased emphasis on power analyses to determine sample size using the G*Power 3 program. Many new data sets and problems. More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages. A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only. Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory. This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers.

This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences.

Methods and Data Analysis for Cross-Cultural Research

Heavy migration patterns, the globalization of markets, and increased cross-cultural communications have made cross-cultural research a necessity in the behavioral and social sciences. This type of research is a natural and inevitable extension for researchers whose earlier focus was on intracultural studies. In Methods and Data Analysis for Cross-Cultural Research, authors Fons Van de Vijver and Kwok Leung have developed a long-awaited guide for graduate students and professionals that presents cross-cultural methodology in a practical light. Covering all the major issues in the field, this volume's presentation of theory serves as a jumping board for the practical discussion of methods, design, and analysis that follows. The central focus is primarily on the design and analysis of quasi-experiments, which is the dominant framework for cross-cultural research. This volume presents an up-to-date overview of the most important tools of cross-cultural research and illustrates the most meaningful techniques in feature boxes, complete with sample data. Professionals and students in the field of cross-cultural research will undoubtedly recognize that this is the most up-to-date and comprehensive practical guide on the market. Students and academics in the fields of clinical/counseling psychology, social work, research methods, sociology, ethnic studies, and social psychology will be grateful for this handy reference when conducting cross-cultural research.

This volume presents an up-to-date overview of the most important tools of cross-cultural research and illustrates the most meaningful techniques in feature boxes, complete with sample data.

Understanding Clinical Data Analysis

Learning Statistical Principles from Published Clinical Research

This textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings. In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs.

The book will cover the WHY-SOs.

Research Methodology and Data Analysis Second Edition

This book provides proper direction in doing research especially towards the understanding of research objectives, and research hypotheses. The book also guides in research methodology such as the methods of designing a questionnaire, methods of sampling, methods of data collection and methods of data analysis. The data analysis covers data mining, descriptive analysis, factor analysis, and reliability analysis. Besides this, the book assesses the normality distribution of data since this is crucial in determining the types of statistical analysis to be employed. More importantly, the book offers guide in analysing the correlational effects, causal effects, mediator effects and also the moderator effect among variables in a model.

This book provides proper direction in doing research especially towards the understanding of research objectives, and research hypotheses.

Statistics and Data Analysis for Nursing Research

The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. Special focus is given to quantitative methods. Other features include management of data, how to "clean" data, and how to work around missing data. New to this edition are updated research examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009.

NEW TO THIS EDITION Emphasis on evidence-based practice - SPSS Version 16.0 was used to generate output for the book - Missing Values are demystified - Factor Analysis content is expanded - Power Analysis methods are explained Additional ...

Data Analysis, Interpretation, and Theory in Literacy Studies Research

A How-To Guide

This research guide addresses the difficulties novice and early career researchers often have with understanding how theory, data analysis and interpretation of findings "hang together" in a well-designed and theorized qualitative research investigation, as well as learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Books that describe data analysis approaches and methods often fail to address the question of how to decide which ones are most appropriate for a particular kind of study, and why they are the best options. This book seeks to clarify these issues in a distinctive way. Chapter authors draw on a successful study they have undertaken and spell out their "problem area," research questions, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they "translated" or interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels.