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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.

Adventures in Social Research

Data Analysis Using SPSS 14.0 and 15.0 for Windows

Designed for both introductory and advanced research methods or statistics courses in sociology, political science, social work, criminal justice, and public health departments, Adventures in Social Research is an ideal computer skills and data analysis textbook for any discipline that uses survey methods. New to the Sixth Edition: - Provides a shorter, more condensed version than the Fifth Edition - Illustrates uses of SPSS 14.0 and new GSS data sets - Includes a CD-ROM that contains data sets, Designing Own Survey and comprehensive appendices that include questionnaires, research reports, proposals, survey tips, commands, readings and more - Offers a Web page that features SPSS version update changes for students and instructors

In this thoroughly revised edition, the authors stress active and collaborative learning as students engage in a series of practical investigative exercises.

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

A Toolkit of Sampling and Data Analysis Techniques for Quantitative Research

Document from the year 2012 in the subject Statistics, grade: -, Monash University Malaysia, Sunway Campus, language: English, comment: Please reference this publication as: Lim, W.M. and Ting, D.H. (2012). Research methodology: a toolkit of sampling and data analysis techniques for quantitative research. GRIN Publishing: Munich, Germany., abstract: Selecting appropriate sampling methods and data analysis techniques for a research study is generally accepted by all researchers in the academia as an imperative component of the research methodology. However, researchers may be encountered with dilemmas when it comes to choosing the most suitable combination of methods to obtain a randomize sample and the best data analysis techniques which are able to project the true state of affairs of the researched phenomenon. This book features a wide range of sampling and data analysis techniques which have been proven to be effectively useful in guiding researchers in the adoption of the most appropriate sampling and data analysis techniques which are in line to accomplish the established research objectives.

This book features a wide range of sampling and data analysis techniques which have been proven to be effectively useful in guiding researchers in the adoption of the most appropriate sampling and data analysis techniques which are in line ...

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

A Tool for Social Research and Data Analysis

Extremely student friendly, Healey's STATISTICS: A TOOL FOR SOCIAL RESEARCH AND DATA ANALYSIS, 11e, equips you with a solid understanding of statistical fundamentals and their practical application to current social issues -- no advanced math knowledge required. The text breaks down even the most complex material to help you master key concepts and develop the skills you need as a professional in a social science field -- or simply to become a "statistically literate" consumer of social research. Everyday examples illustrate that statistics are not just abstract mathematical constructs, but they have practical value in government, education, business, media, politics, sports and more. Research examples in every chapter include the same "real data" used by professionals across various fields to make evidence-based decisions. Also available: MindTap digital learning solution.

The text breaks down even the most complex material to help you master key concepts and develop the skills you need to succeed as a professional in a social science field -- or simply to become a statistically literate consumer of social ...

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 ...

Advanced Statistics in Research

Reading, Understanding, and Writing Up Data Analysis Results

"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

Advanced Statistics in Research: Reading, Understanding and Writing Up Data Anaylsis Results; makes multivariate statistics accessible to all readers--including those with little training in research or data analysis; Advanced Statistics in ...