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
22 - Foundational Issues
from Part III - Elements of Statistical Inference
Published online by Cambridge University Press: 22 July 2022
- 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
Randomization was presented in a previous chapter as an essential ingredient in the collection of data, both in survey sampling and in experimental design. We argue here that randomization is the essential foundation of statistical inference: It leads to conditional inference in an almost canonical way, and allows for causal inference, which are the two topics covered in the chapter.
- Type
- Chapter
- Information
- Principles of Statistical AnalysisLearning from Randomized Experiments, pp. 356 - 370Publisher: Cambridge University PressPrint publication year: 2022