Social Science Research Design and Statistics

A Practitioner's Guide to Research Methods and IBM SPSS

Author: Alfred P. Rovai

Publisher: Watertree Press LLC

ISBN:

Category: Computers

Page: 556

View: 778

This book integrates social science research methods and the descriptions of over 40 univariate, bivariate, and multivariate tests to include a description of the purpose, key assumptions and requirements, example research question and null hypothesis, SPSS procedures, display and interpretation of SPSS output, and what to report for each test. It is classroom tested and current with IBM SPSS 22. This expanded second edition also features companion website materials including copies of the IBM SPSS datasets used to create the SPSS output presented in the book, and Microsoft PowerPoint presentations that display step-by-step instructions on how to run popular SPSS procedures. Included throughout the book are various sidebars highlighting key points, images and SPSS screenshots to assist understanding the material presented, self-test reviews at the end of each chapter, a decision tree to facilitate identification of the proper statistical test, examples of SPSS output with accompanying analysis and interpretations, links to relevant web sites, and a comprehensive glossary. Underpinning all these features is a concise, easy to understand explanation of the material.

Socioeconomic Factors and Outcomes in Higher Education

A Multivariate Analysis

Author: Carlos Felipe Rodríguez Hernández

Publisher: Universidad externado de Colombia

ISBN:

Category: Education

Page: 113

View: 325

In the Colombian case, it is very common to associate academic performance with the students' socioeconomic conditions. A generalized and bivariate interpretation of this relationship could imply that only students from a high socioeconomic class would perform satisfactorily and that all students from a low socioeconomic class would perform poorly. If this is the case, then the educational system could be increasing the gap between social classes instead of making it smaller. Therefore, it seems important to examine the way in which some socioeconomic factors are related to the students' academic performance in Colombia. Consequently, Socioeconomic Factors and Outcomes in Higher Education: a Multivariate Analysis, explores the relationship between the results in standardized tests and socioeconomic variables in a cohort of Colombian students.

The Influence of Information Order Effects and Trait Professional Skepticism on Auditors’ Belief Revisions

A Theoretical and Empirical Analysis

Author: Kristina Yankova

Publisher: Springer

ISBN:

Category: Business & Economics

Page: 302

View: 841

Kristina Yankova addresses the question of what role professional skepticism plays in the context of cognitive biases (the so-called information order effects) in auditor judgment. Professional skepticism is a fundamental concept in auditing. Despite its immense importance to audit practice and the voluminous literature on this issue, professional skepticism is a topic which still involves more questions than answers. The work provides important theoretical and empirical insights into the behavioral implications of professional skepticism in auditing.

A Concise Guide to Market Research

The Process, Data, and Methods Using IBM SPSS Statistics

Author: Erik Mooi

Publisher: Springer Science & Business Media

ISBN:

Category: Business & Economics

Page: 308

View: 939

This accessible, practice-oriented and compact text provides a hands-on introduction to the principles of market research. Using the market research process as a framework, the authors explain how to collect and describe the necessary data and present the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis, and cluster analysis. An explanation is provided of the theoretical choices a market researcher has to make with regard to each technique, as well as how these are translated into actions in IBM SPSS Statistics. This includes a discussion of what the outputs mean and how they should be interpreted from a market research perspective. Each chapter concludes with a case study that illustrates the process based on real-world data. A comprehensive web appendix includes additional analysis techniques, datasets, video files and case studies. Several mobile tags in the text allow readers to quickly browse related web content using a mobile device.

A Concise Guide to Market Research

The Process, Data, and Methods Using IBM SPSS Statistics

Author: Marko Sarstedt

Publisher: Springer

ISBN:

Category: Business & Economics

Page: 347

View: 303

This accessible, practice-oriented and compact text provides a hands-on introduction to market research. Using the market research process as a framework, it explains how to collect and describe data and presents the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis and cluster analysis. The book describes the theoretical choices a market researcher has to make with regard to each technique, discusses how these are converted into actions in IBM SPSS version 22 and how to interpret the output. Each chapter concludes with a case study that illustrates the process using real-world data. A comprehensive Web appendix includes additional analysis techniques, datasets, video files and case studies. Tags in the text allow readers to quickly access Web content with their mobile device. The new edition features: Stronger emphasis on the gathering and analysis of secondary data (e.g., internet and social networking data) New material on data description (e.g., outlier detection and missing value analysis) Improved use of educational elements such as learning objectives, keywords, self-assessment tests, case studies, and much more Streamlined and simplified coverage of the data analysis techniques with more rules-of-thumb Uses IBM SPSS version 22

Performing Data Analysis Using IBM SPSS

Author: Lawrence S. Meyers

Publisher: John Wiley & Sons

ISBN:

Category: Mathematics

Page: 736

View: 882

Features easy-to-follow insight and clear guidelines to performdata analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquelyaddresses the presented statistical procedures with an exampleproblem, detailed analysis, and the related data sets. Data entryprocedures, variable naming, and step-by-step instructions for allanalyses are provided in addition to IBM SPSS point-and-clickmethods, including details on how to view and manipulateoutput. Designed as a user’s guide for students and otherinterested readers to perform statistical data analysis with IBMSPSS, this book addresses the needs, level of sophistication, andinterest in introductory statistical methodology on the part ofreaders in social and behavioral science, business, health-related,and education programs. Each chapter of Performing Data AnalysisUsing IBM SPSS covers a particular statistical procedure andoffers the following: an example problem or analysis goal, togetherwith a data set; IBM SPSS analysis with step-by-step analysis setupand accompanying screen shots; and IBM SPSS output with screenshots and narrative on how to read or interpret the results of theanalysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output Descriptive statistics procedures Score distribution assumption evaluations Bivariate correlation Regressing (predicting) quantitative and categoricalvariables Survival analysis t Test ANOVA and ANCOVA Multivariate group differences Multidimensional scaling Cluster analysis Nonparametric procedures for frequency data Performing Data Analysis Using IBM SPSS is an excellenttext for upper-undergraduate and graduate-level students in courseson social, behavioral, and health sciences as well as secondaryeducation, research design, and statistics. Also an excellentreference, the book is ideal for professionals and researchers inthe social, behavioral, and health sciences; applied statisticians;and practitioners working in industry.

Single-case and Small-n Experimental Designs

A Practical Guide To Randomization Tests, Second Edition

Author: Pat Dugard

Publisher: Taylor & Francis

ISBN:

Category: Psychology

Page: 304

View: 687

This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the book’s website so that users can run analyses of the text data as well as data from their own studies. The new edition features: More explanation as to why randomization tests are useful and how to apply them. More varied and expanded examples that demonstrate the use of these tests in education, clinical work and psychology. A website with the macros and datasets for all of the text examples in IBM SPSS and Excel. Exercises at the end of most chapters that help readers test their understanding of the material. A new glossary that defines the key words that appear in italics when they are first introduced. A new appendix that reviews the basic skills needed to do randomization tests. New appendices that provide annotated SPSS and Excel macros to help readers write their own or tinker with the ones provided in the book. The book opens with an overview of single case and small n designs -- why they are needed and how they differ from descriptive case studies. Chapter 2 focuses on the basic concepts of randoization tests. Next how to choose and implement a randomization design is reviewed including material on how to perform the randomizations, how to select the number of observations, and how to record the data. Chapter 5 focuses on how to analyze the data including how to use the macros and understand the results. Chapter 6 shows how randomization tests fit into the body of statistical inference. Chapter 7 discusses size and power. The book concludes with a demonstration of how to edit or modify the macros or use parts of them to write your own. Ideal as a text for courses on single-case, small n design, and/or randomization tests taught at the graduate level in psychology (especially clinical, counseling, educational, and school), education, human development, nursing, and other social and health sciences, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this book’s accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.

Repeated Measures Design for Empirical Researchers

Author: J. P. Verma

Publisher: John Wiley & Sons

ISBN:

Category: Science

Page: 288

View: 498

Introduces the applications of repeated measures design processes with the popular IBM® SPSS® software Repeated Measures Design for Empirical Researchers presents comprehensive coverage of the formation of research questions and the analysis of repeated measures using IBM SPSS and also includes the solutions necessary for understanding situations where the designs can be used. In addition to explaining the computation involved in each design, the book presents a unique discussion on how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes. Featuring practical examples from a multitude of domains including psychology, the social sciences, management, and sports science, the book helps readers better understand the associated theories and methodologies of repeated measures design processes. The book covers various fundamental concepts involved in the design of experiments, basic statistical designs, computational details, differentiating independent and repeated measures designs, and testing assumptions. Along with an introduction to IBM SPSS software, Repeated Measures Design for Empirical Researchers includes: A discussion of the popular repeated measures designs frequently used by researchers, such as one-way repeated measures ANOVA, two-way repeated measures design, two-way mixed design, and mixed design with two-way MANOVA Coverage of sample size determination for the successful implementation of designing and analyzing a repeated measures study A step-by-step guide to analyzing the data obtained with real-world examples throughout to illustrate the underlying advantages and assumptions A companion website with supplementary IBM SPSS data sets and programming solutions as well as additional case studies Repeated Measures Design for Empirical Researchers is a useful textbook for graduate- and PhD-level students majoring in biostatistics, the social sciences, psychology, medicine, management, sports, physical education, and health. The book is also an excellent reference for professionals interested in experimental designs and statistical sciences as well as statistical consultants and practitioners from other fields including biological, medical, agricultural, and horticultural sciences. J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics. He is the author of Statistics for Exercise Science and Health with Microsoft® Office Excel®, also published by Wiley.

Research Methods in Business Studies

A Practical Guide

Author: Pervez N. Ghauri

Publisher: Financial Times/Prentice Hall

ISBN:

Category: Business & Economics

Page: 162

View: 845

This guide demonstrates to students the importance of a scientific approach to business research and problem-solving projects. It shows how to formulate a problem and choose a research method, and how to argue and motivate. The book discusses the practicalities of research such as problem formulation, relating the research to previous studies, choosing the right methodology, presentation of results, report writing and drawing conclusions. This work is intended for MBA/MSc and undergraduate students doing business studies, business administration, economics, finance and marketing courses. Consultants and organizations undertaking research in business studies should also find this a useful text.

Single-case and Small-n Experimental Designs

A Practical Guide to Randomization Tests

Author: John B. Todman

Publisher: Psychology Press

ISBN:

Category: Mathematics

Page: 245

View: 422

This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the bookâe(tm)s website so that users can run analyses of the text data as well as data from their own studies. The new edition features: More explanation as to why randomization tests are useful and how to apply them. More varied and expanded examples that demonstrate the use of these tests in education, clinical work and psychology. A website with the macros and datasets for all of the text examples in IBM SPSS and Excel. Exercises at the end of most chapters that help readers test their understanding of the material. A new glossary that defines the key words that appear in italics when they are first introduced. A new appendix that reviews the basic skills needed to do randomization tests. New appendices that provide annotated SPSS and Excel macros to help readers write their own or tinker with the ones provided in the book. The book opens with an overview of single case and small n designs -- why they are needed and how they differ from descriptive case studies. Chapter 2 focuses on the basic concepts of randoization tests. Next how to choose and implement a randomization design is reviewed including material on how to perform the randomizations, how to select the number of observations, and how to record the data. Chapter 5 focuses on how to analyze the data including how to use the macros and understand the results. Chapter 6 shows how randomization tests fit into the body of statistical inference. Chapter 7 discusses size and power. The book concludes with a demonstration of how to edit or modify the macros or use parts of them to write your own. Ideal as a text for courses on single-case, small n design, and/or randomization tests taught at the graduate level in psychology (especially clinical, counseling, educational, and school), education, human development, nursing, and other social and health sciences, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this bookâe(tm)s accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.