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
17 - Multiple Numerical Samples
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 that yields, as data, a sample of independent and identically distributed (real-valued) random variables with a common distribution on the real line. The estimation of the underlying mean and median is discussed at length, and bootstrap confidence intervals are constructed. Tests comparing the underlying distribution to a given distribution (e.g., the standard normal distribution) or a family of distribution (e.g., the normal family of distributions) are introduced. Censoring, which is very common in some clinical trials, is briefly discuss.
- Type
- Chapter
- Information
- Principles of Statistical AnalysisLearning from Randomized Experiments, pp. 271 - 288Publisher: Cambridge University PressPrint publication year: 2022