Introduction to Quantitative Research Methods is a student-friendly introduction to quantitative research methods and basic statistics. It uses a detective theme throughout the text to show how quantitative methods have been used to solve real-life problems. The book focuses on principles and techniques that are appropriate to introductory level courses in media, psychology and sociology. Examples and illustrations are drawn from historical and contemporary research in the social sciences. The original CD-ROM accompanying the book and its content are no longer available.
"The book provides a reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research..." —Megan Tschannen-Moran, The College of William & Mary Quantitative Research in Education: A Primer, Second Edition is a brief and practical text designed to allay anxiety about quantitative research. Award-winning authors Wayne K. Hoy and Curt M. Adams first introduce readers to the nature of research and science, and then present the meaning of concepts and research problems as they dispel notions that quantitative research is too difficult, too theoretical, and not practical. Rich with concrete examples and illustrations, the Primer emphasizes conceptual understanding and the practical utility of quantitative methods while teaching strategies and techniques for developing original research hypotheses. The Second Edition includes suggestions for empirical investigation and features a new section on self-determination theory, examples from the latest research, a concluding chapter illustrating the practical applications of quantitative research, and much more. This accessible Primer is perfect for students and researchers who want a quick understanding of the process of scientific inquiry and who want to learn how to effectively create and test ideas.
Quantitative and Statistical Research Methods This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to: Pinpoint research questions and hypotheses Identify, classify, and operationally define the study variables Choose appropriate research designs Conduct power analysis Select an appropriate statistic for the problem Use a data set Conduct data screening and analyses using SPSS Interpret the statistics Write the results related to the problem Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.
One key responsibility of product designers and UX practitioners is to conduct formal and informal research to clarify design decisions and business needs. But there’s often mystery around product research, with the feeling that you need to be a research Zen master to gather anything useful. Fact is, anyone can conduct product research. With this quick reference guide, you’ll learn a common language and set of tools to help you carry out research in an informed and productive manner. This book contains four sections, including a brief introduction to UX research, planning and preparation, facilitating research, and analysis and reporting. Each chapter includes a short exercise so you can quickly apply what you’ve learned. Learn what it takes to ask good research questions Know when to use quantitative and qualitative research methods Explore the logistics and details of coordinating a research session Use softer skills to make research seem natural to participants Learn tools and approaches to uncover meaning in your raw data Communicate your findings with a framework and structure
For more than 40 years, SAGE has been one of the leading international publishers of works on quantitative research methods in the social sciences. This new collection provides readers with a representative sample of the best articles in quantitative methods that have appeared in SAGE journals as chosen by W. Paul Vogt, editor of other successful major reference collections such as Selecting Research Methods (2008) and Data Collection (2010). The volumes and articles are organized by theme rather than by discipline. Although there are some discipline-specific methods, most often quantitative research methods cut across disciplinary boundaries. Volume One: Fundamental Issues in Quantitative Research Volume Two: Measurement for Causal and Statistical Inference Volume Three: Alternatives to Hypothesis Testing Volume Four: Complex Designs for a Complex World
Quantitative methodology is a highly specialized field, and as with any highly specialized field, working through idiosyncratic language can be very difficult made even more so when concepts are conveyed in the language of mathematics and statistics. The Sage Handbook of Quantitative Methodology for the Social Sciences was conceived as a way of introducing applied statisticians, empirical researchers, and graduate students to the broad array of state-of-the-art quantitative methodologies in the social sciences. The contributing authors of the Handbook were asked to write about their areas of expertise in a way that would convey to the reader the utility of their respective methodologies. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter. The Handbook consists of six sections comprising twenty-five chapters, from topics in scaling and measurement, to advances in statistical modelling methodologies, and finally to broad philosophical themes that transcend many of the quantitative methodologies covered in this handbook.
The bestseller that pioneered the comparison of qualitative, quantitative, and mixed methods research design continues in its Fourth Edition to help students and researchers prepare their plan or proposal for a scholarly journal article, dissertation or thesis.
This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book′s website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.
Attempting to describe quantitative research methods through one volume of material is quite a challenging endeavor and it should be noted here that this book is by no means attempting to exhaustively present everything under the Sun on the subject. Interested readers will need to expand on what is presented here by searching the extant literature on what exists and what best suits their research needs. Having said that, the book does cover the great majority of quantitative methods found in social sciences research.The motivation for developing this book came from years of delivering quantitative methods courses for graduate programs in Europe and the USA. Through exposure to such programs it became apparent that while most students had some exposure, to statistics mainly, at the time they entered graduate studies most of their understanding and familiarity with quantitative techniques was forgotten or vaguely remembered. In many cases, what remained was the impression of how much they "hated" the subject. Overcoming this negative predisposition required a re-introduction of basic concepts and a fast-track approach to higher and more advanced methods of analysis.These realities guided the development of this book and so the assumption is made that the reader doesn't know anything about quantitative research and about research in general. All concepts presented in the book are defined and introduced. Also, alternative and overlapping expressions and keywords used in quantitative research are presented so the reader can identify them in their readings of academic research. Whether this "zero-to-hero" approach succeeded is left for the reader to judge.Additional effort was made to include examples that are easily replicated in spreadsheets like Excel so the users can manually repeat them at their convenience. Regarding the use of software, commands for executing the various methods for SPSS are given in footnotes to avoid diverting from the core narrative of the text. The interested reader can easily retrieve a plethora of material from the Internet with step-by-step instructions for most of the analysis techniques discussed here and for the most popular statistical software packages. The book's website at www.harkiolakis.com/books/quan provides additional material for executing the methods discussed here with SPSS, as well as all book images in higher resolution and links to other sources online. For instructors who are interested in using the book as a textbook, data sets and exercises on the methods included in the book are available upon request.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
