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Statistics in a Nutshellby Sarah Boslaugh
Synopses & Reviews
Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts.
Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.
About the Author
Sarah Boslaugh holds a PhD in Research and Evaluation from the City University of New York and have been working as a statistical analyst for 15 years, in a variety of professional settings, including the New York City Board of Education, the Institutional Research Office of the City University of New York, Montefiore Medical Center, the Virginia Department of Social Services, Magellan Health Services, Washington University School of Medicine, and BJC HealthCare. She has taught statistics in several different contexts and currently teaches Intermediate Statistics at Washington University Medical School. She has published two previous books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE Publications, 2004) and Secondary Data Sources for Public Health (forthcoming from Cambridge U. Press, 2007) and am currently editing the Encyclopedia of Epidemiology for SAGE Publications (forthcoming, 2007).
Table of Contents
PrefaceChapter 1: Basic Concepts of MeasurementChapter 2: ProbabilityChapter 3: Inferential StatisticsChapter 4: Descriptive Statistics and Graphic DisplaysChapter 5: Categorical DataChapter 6: The t-TestChapter 7: The Pearson Correlation CoefficientChapter 8: Introduction to Regression and ANOVAChapter 9: Factorial ANOVA and ANCOVAChapter 10: Multiple Linear RegressionChapter 11: Logistic, Multinomial, and Polynomial RegressionChapter 12: Factor Analysis, Cluster Analysis, and Discriminant Function AnalysisChapter 13: Nonparametric StatisticsChapter 14: Business and Quality Improvement StatisticsChapter 15: Medical and Epidemiological StatisticsChapter 16: Educational and Psychological StatisticsChapter 17: Data ManagementChapter 18: Research DesignChapter 19: Communicating with StatisticsChapter 20: Critiquing Statistics Presented by OthersReview of Basic MathematicsIntroduction to Statistical PackagesReferencesProbability Tables for Common DistributionsOnline ResourcesGlossary of Statistical TermsColophon
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