FINK: HOW TO ANALYZE SURVEY (PAPER) DATA (Survey Kit, 8, Band 8) - Softcover

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Arlene Fink (PhD) is Professor of Medicine and Public Health at the University of California, Los Angeles, and president of the Langley Research Institute. Her main interests include evaluation and survey research and the conduct of research literature reviews as well as the evaluation of their quality. Dr. Fink has conducted scores of evaluation studies in public health, medicine, and education. She is on the faculty of UCLA's Robert Wood Johnson Clinical Scholars Program and is a scientific and evaluation advisor to UCLA's Gambling Studies and IMPACT (Improving Access, Counseling & Treatment for Californians with Prostate Cancer) programs. She consults nationally and internationally for agencies such as L'institut de Promotion del la Prévention Secondaire en Addictologie (IPPSA) in Paris, France, and Peninsula Health in Victoria, Australia. Professor Fink has taught and lectured extensively all over the world and is the author of more than 130 peer-reviewed articles and 15 textbooks.

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"This is a very basic overview of statistical terms and tests with which any persons conducting a survey should be familiar if a survey is to be appropriately designed and analyzed. The presentation is straightforward and uses numerous appropriate examples and exercises to illustrate ideas. These materials could be used with a wide range of audiences. I would be inclined to include this in my graduate methods class because many students take the methods course before thy have completed the series of statistics courses. For those students who have completed a statistic course, this book can serve as a very nice primer for guiding their decisions in survey design and analysis."

--Rhonda J. V. Montgomery, Department of Gerontology, University of Kansas

Clear and concise, How to Analyze Survey Data shows you how to do just that: analyze survey data. Beginning with a basic overview, this volume shows what statistics can do for surveys, describes measurement scales in detail, and demonstrates how to choose a method to analyze your results. It includes checklists and guidelines, and practice exercises to check your progress. The volume also discusses regression, hypothesis testing, and offers a cogent discussion on screening and transforming data.