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Research Methods in Applied Settings: An Integrated Approach to Design and Analysis
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 master’s 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.
This extensively revised edition features more than 50% new material including:
488 pages, Kindle Edition
Published March 17, 2011
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December 30, 2017
A good reference text on quantitative research design from a postpositivistic philosophical orientation that positions reality as static and knowable. Some parts were not updated with the new release, specifically around validity, but the text is an overall solid resource for methodology students and any MS/PhD students conducting quantitative research. Provides strong heuristics for designing and evaluating research.
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