Through its integrated approach to quantitative research methods, this text teaches readers how to plan, conduct, and write a research project and select and interpret data so they can become better consumers of research. This is not a statistics book-there are very few formulas. Rather, this book helps students master which statistic to use when and how to interpret the results. Organized around the steps one takes in conducting a research project, this book is ideal for applied programs and for those who want to analyze ...
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Through its integrated approach to quantitative research methods, this text teaches readers how to plan, conduct, and write a research project and select and interpret data so they can become better consumers of research. This is not a statistics book-there are very few formulas. Rather, this book helps students master which statistic to use when and how to interpret the results. Organized around the steps one takes in conducting a research project, this book is ideal for applied programs and for those who want to analyze and evaluate research articles. Having taught in a variety of departments, the authors have a good grasp of the research problems faced by masters and doctoral students in diverse areas of the behavioral and social sciences. Text adopters applaud the book's clarity. Students are often confused by other texts' use of inconsistent terminology. To avoid this confusion, the authors present a semantically consistent picture that emphasizes five research approaches-- randomized experimental, quasi-experimental, comparative, associational, and descriptive. The authors then show how these approaches lead to three kinds of research designs which, in turn, lead to three groups of statistics with the same names. This consistent framework increases comprehension and the ability to apply the material. Numerous applied problems, annotated examples, and diagrams and tables further promote comprehension. Although the book emphasizes quantitative research, the value of qualitative research is introduced. Each chapter also features boldfaced key terms, chapter introductions and summaries, interpretation questions, updated and additional examples, and boxes that highlight discussions of actual research projects from multiple disciplines. This extensively revised edition features: -A richer pedagogical plan including interpretation questions, 2-3 real-life examples per chapter, and boxes that highlight discussions of actual research projects from multiple disciplines. -More coverage of research problems and reviewing the literature (Ch. 2). -A new discussion on estimation for true score in classical test theory (ch 11) and how it is computed (ch 15). -More of the basics on the traditional ways to think about measurement validity to clarify what is meant by evidence based response processes (ch 12). -More information on conflict of interest and commitment, authorship, security of data, saving original files, and password protecting data files (ch 14). -Expanded section on how conflict of interests can lead to bias in data coding and analysis along with suggestions for how to deal with potential bias (ch 14). -New information on data transformations including how to use continuous data to create categorical data classifications such as high risk and low risk (ch. 15). -Expanded section on different designs now includes a sample methods section and more information on multiple and logistic regression, mediation, and moderation analysis (ch. 22). - A new table that highlights what to include in parts of an APA research paper (Ch 27). -Updated list of suggested readings including contemporary articles and articles students can critique for class (Appendix A). -A new appendix that includes 2-3 results write-up examples (Appendix G).
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New. Print on demand Contains: Illustrations, black & white, Tables, black & white. Includes: illustrations, black & white, tables, black & white. Intended for college/higher education audience.
