## Book description

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

## Publisher resources

View/Submit Errata

1. Statistics in a Nutshell
2. SPECIAL OFFER: Upgrade this ebook with O’Reilly
3. Preface
4. 1. Basic Concepts of Measurement
1. Measurement
2. Levels of Measurement
3. True and Error Scores
4. Reliability and Validity
5. Measurement Bias
6. Exercises
5. 2. Probability
2. Basic Definitions
3. Defining Probability
1. Expressing the Probability of an Event
2. Conditional Probabilities
3. Calculating the Probability of Multiple Events
4. Bayes’ Theorem
5. Enough Exposition, Let’s Do Some Statistics!
6. Exercises
6. 3. Inferential Statistics
1. Probability Distributions
2. Independent and Dependent Variables
3. Populations and Samples
4. The Central Limit Theorem
5. Hypothesis Testing
6. Confidence Intervals
7. p-values
8. The Z-Statistic
9. Data Transformations
10. Exercises
7. 4. Descriptive Statistics and Graphic Displays
1. Populations and Samples
2. Measures of Central Tendency
3. Measures of Dispersion
4. Outliers
5. Graphic Methods
6. Bar Charts
7. Bivariate Charts
8. Exercises
8. 5. Categorical Data
1. The R×C Table
2. The Chi-Square Distribution
3. The Chi-Square Test
4. Fisher’s Exact Test
5. McNemar’s Test for Matched Pairs
6. Proportions: The Large Sample Case
7. Correlation Statistics for Categorical Data
8. The Likert and Semantic Differential Scales
9. Exercises
9. 6. The t-Test
1. The t Distribution
2. The One-Sample t-Test
3. The Independent Samples t-Test
4. Repeated Measures t-Test
5. Unequal Variance t-Test
6. Exercises
10. 7. The Pearson Correlation Coefficient
1. Association
2. Scatterplots
3. The Pearson Correlation Coefficient
4. The Coefficient of Determination
5. Exercises
11. 8. Introduction to Regression and ANOVA
1. The General Linear Model
2. Linear Regression
3. Analysis of Variance (ANOVA)
4. Calculating Simple Regression by Hand
5. Exercises
12. 9. Factorial ANOVA and ANCOVA
1. Factorial ANOVA
2. ANCOVA
3. Exercises
13. 10. Multiple Linear Regression
1. Multiple Regression Models
1. Dummy Variables
2. Methods for Building Regression Models
2. Exercises
14. 11. Logistic, Multinomial, and Polynomial Regression
1. Logistic Regression
2. Multinomial Logistic Regression
3. Polynomial Regression
4. Overfitting
5. Exercises
15. 12. Factor Analysis, Cluster Analysis, and Discriminant Function Analysis
16. 13. Nonparametric Statistics
1. Between-Subjects Designs
2. Within-Subjects Designs
3. Exercises
17. 14. Business and Quality Improvement Statistics
1. Index Numbers
2. Time Series
3. Decision Analysis
4. Quality Improvement
5. Exercises
18. 15. Medical and Epidemiological Statistics
1. Measures of Disease Frequency
2. Ratio, Proportion, and Rate
3. Prevalence and Incidence
4. Crude, Category-Specific, and Standardized Rates
5. The Risk Ratio
6. The Odds Ratio
7. Confounding, Stratified Analysis, and the Mantel-Haenszel Common Odds Ratio
8. Power Analysis
9. Sample Size Calculations
10. Exercises
19. 16. Educational and Psychological Statistics
1. Percentiles
2. Standardized Scores
3. Test Construction
4. Classical Test Theory: The True Score Model
5. Reliability of a Composite Test
6. Measures of Internal Consistency
7. Item Analysis
8. Item Response Theory
9. Exercises
20. 17. Data Management
21. 18. Research Design
1. Basic Vocabulary
2. Observational Studies
3. Quasi-Experimental Studies
4. Experimental Studies
5. Gathering Experimental Data
6. Example Experimental Design
22. 19. Communicating with Statistics
1. General Notes
23. 20. Critiquing Statistics Presented by Others
1. Evaluating the Whole Article
2. The Misuse of Statistics
3. Common Problems
4. Quick Checklist
5. Issues in Research Design
6. Descriptive Statistics
7. Inferential Statistics
1. Assumptions of Statistical Tests
24. A. Review of Basic Mathematics
1. Laws of Arithmetic
2. Properties of Real Numbers
3. Exponents and Roots
4. Solving Equations
5. Systems of Equations
6. Graphing Equations
7. Linear Inequalities
8. Fractions
9. Factorials, Permutations, and Combinations
10. Exercises
25. B. Introduction to Statistical Packages
26. C. References
27. D. Probability Tables for Common Distributions
28. E. Online Resources
29. F. Glossary of Statistical Terms
30. Index