# Statistics in a Nutshell

"O'Reilly Media, Inc.", Nov 15, 2012 - Mathematics - 569 pages
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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

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I do not recall the exact number of people she fed everyday

### Contents

 Chapter 1 Basic Concepts of Measurement 1 Chapter 2 Probability 21 Chapter 3 Inferential Statistics 45 Chapter 4 Descriptive Statistics and Graphic Displays 83 Chapter 5 Categorical Data 121 Chapter 6 The tTest 155 Chapter 7 The Pearson Correlation Coefficient 173 Chapter 8 Introduction to Regression and ANOVA 193
 Chapter 15 Medical and Epidemiological Statistics 351 Chapter 16 Educational and Psychological Statistics 385 Chapter 17 Data Management 411 Chapter 18 Research Design 425 Chapter 19 Communicating with Statistics 449 Chapter 20 Critiquing Statistics Presented by Others 457 Appendix A Review of Basic Mathematics 473 Appendix B Introduction to Statistical Packages 499

 Chapter 9 Factorial ANOVA and ANCOVA 223 Chapter 10 Multiple Linear Regression 243 Chapter 11 Logistic Multinomial and Polynomial Regression 273 Chapter 12 Factor Analysis Cluster Analysis and Discriminant Function Analysis 291 Chapter 13 Nonparametric Statistics 307 Chapter 14 Business and Quality Improvement Statistics 325
 Appendix C References 513 Appendix D Probability Tables for Common Distributions 527 Appendix E Online Resources 539 Appendix F Glossary of Statistical Terms 543 Index 553 Copyright

### About the author (2012)

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).