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.…mehr
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. Learn basic concepts of measurement and probability theory, data management, and research design Discover basic statistical procedures, including correlation, the t-test, the chi-square and Fisher's exact tests, and techniques for analyzing nonparametric data Learn advanced techniques based on the general linear model, including ANOVA, ANCOVA, multiple linear regression, and logistic regression Use and interpret statistics for business and quality improvement, medical and public health, and education and psychology Communicate with statistics and critique statistical information presented by others
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).
Inhaltsangabe
Preface Chapter 1: Basic Concepts of Measurement Chapter 2: Probability Chapter 3: Inferential Statistics Chapter 4: Descriptive Statistics and Graphic Displays Chapter 5: Categorical Data Chapter 6: The t-Test Chapter 7: The Pearson Correlation Coefficient Chapter 8: Introduction to Regression and ANOVA Chapter 9: Factorial ANOVA and ANCOVA Chapter 10: Multiple Linear Regression Chapter 11: Logistic, Multinomial, and Polynomial Regression Chapter 12: Factor Analysis, Cluster Analysis, and Discriminant Function Analysis Chapter 13: Nonparametric Statistics Chapter 14: Business and Quality Improvement Statistics Chapter 15: Medical and Epidemiological Statistics Chapter 16: Educational and Psychological Statistics Chapter 17: Data Management Chapter 18: Research Design Chapter 19: Communicating with Statistics Chapter 20: Critiquing Statistics Presented by Others Review of Basic Mathematics Introduction to Statistical Packages References Probability Tables for Common Distributions Online Resources Glossary of Statistical Terms Colophon
Preface Chapter 1: Basic Concepts of Measurement Chapter 2: Probability Chapter 3: Inferential Statistics Chapter 4: Descriptive Statistics and Graphic Displays Chapter 5: Categorical Data Chapter 6: The t-Test Chapter 7: The Pearson Correlation Coefficient Chapter 8: Introduction to Regression and ANOVA Chapter 9: Factorial ANOVA and ANCOVA Chapter 10: Multiple Linear Regression Chapter 11: Logistic, Multinomial, and Polynomial Regression Chapter 12: Factor Analysis, Cluster Analysis, and Discriminant Function Analysis Chapter 13: Nonparametric Statistics Chapter 14: Business and Quality Improvement Statistics Chapter 15: Medical and Epidemiological Statistics Chapter 16: Educational and Psychological Statistics Chapter 17: Data Management Chapter 18: Research Design Chapter 19: Communicating with Statistics Chapter 20: Critiquing Statistics Presented by Others Review of Basic Mathematics Introduction to Statistical Packages References Probability Tables for Common Distributions Online Resources Glossary of Statistical Terms Colophon
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