Statistics in a Nutshell

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"O'Reilly Media, Inc.", Nov 10, 2012 - Mathematics - 594 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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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
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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).

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