The third edition of PDQ Statistics provides an overview of all major statistical methods, giving the reader a good understanding of statistics and how they are used in research articles. It covers the major categories - variable and descriptive statistics, parametric statistics, non-parametric statistics, and multivariate statistics. The explanations are clear, succinct, and loaded with practical examples.
Autorentext
Geoffrey R. Norman, PhD is Professor of Clinical Epidemiology and Biostatistics at McMaster University, Hamilton, Ontario, Canada
Inhalt
Contents
Preface
Introduction
Part One Variables and Descriptive Statistics
Chapter 1. Names and Numbers: Types of Variables
Chapter 2. Describing Data
Part Two Parametric Statistics
Chapter 3. Statistical Inference
Chapter 4. Comparison of Means of Two Samples: The t Test
Chapter 5. Comparison among Many Means: Analysis of Variance
Chapter 6. Relationship between Interval and Ratio Variables: Linear and Multiple Regression
Chapter 7. Analysis of Covariance
Chapter 8. Variations on Linear Regression: Logistic Regression, General Linear Model, and Hierarchical Linear Models
Chapter 9. Time Series Analysis
Part Three Nonparametric Statistics
Chapter 10. Nonparametric Tests of Significance
Chapter 11. Nonparametric Measures of Association
Chapter 12. Advanced Nonparametric Methods
Part Four Multivariate Statistics
Chapter 13. Introduction to Multivariate Statistics
Chapter 14. Multivariate Analysis of Variance
Chapter 15. Discriminant Function Analysis
Chapter 16. Exploratory Factor Analysis
Chapter 17. Path Analysis and Structural Equation Modeling
Chapter 18. Cluster Analysis
Canonical Correlation
Reprise
Research Designs
Index
Unabashed Glossary