Book contents
- Frontmatter
- Dedication
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Part I Elements of Probability Theory
- Part II Practical Considerations
- Part III Elements of Statistical Inference
- 12 Models, Estimators, and Tests
- 13 Properties of Estimators and Tests
- 14 One Proportion
- 15 Multiple Proportions
- 16 One Numerical Sample
- 17 Multiple Numerical Samples
- 18 Multiple Paired Numerical Samples
- 19 Correlation Analysis
- 20 Multiple Testing
- 21 Regression Analysis
- 22 Foundational Issues
- References
- Index
19 - Correlation Analysis
from Part III - Elements of Statistical Inference
Published online by Cambridge University Press: 22 July 2022
Book contents
- Frontmatter
- Dedication
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Part I Elements of Probability Theory
- Part II Practical Considerations
- Part III Elements of Statistical Inference
- 12 Models, Estimators, and Tests
- 13 Properties of Estimators and Tests
- 14 One Proportion
- 15 Multiple Proportions
- 16 One Numerical Sample
- 17 Multiple Numerical Samples
- 18 Multiple Paired Numerical Samples
- 19 Correlation Analysis
- 20 Multiple Testing
- 21 Regression Analysis
- 22 Foundational Issues
- References
- Index
Summary
We consider an experiment resulting in two paired numerical variables. The general goal addressed in this chapter is that of quantifying the strength of association between these two variables. By association we mean dependence. Contrary to the previous chapter, here the two variables can be measurements of completely different kinds (e.g., height and weight). Several measures of association are introduced, and used to test for independence.
- Type
- Chapter
- Information
- Principles of Statistical AnalysisLearning from Randomized Experiments, pp. 299 - 308Publisher: Cambridge University PressPrint publication year: 2022