224 Pages
35 B/W Illustrations
by
Chapman & Hall
224 Pages
35 B/W Illustrations
by
Chapman & Hall
Also available as eBook on:
An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression.... Read more
Background
One-Sample Nonparametric Inference
Two-Sample Testing
Methods for Three or More Groups
Group Differences with Blocking
Bivariate Methods
Multivariate Analysis
Density Estimation
Regression Function Estimates
Resampling Techniques
Appendices
Biography
John Kolassa is Professor of Statistics and Biostatistics, Rutgers, the State University of New Jersey.
'In my opinion, nonparametric tests, proposed in the book can be applied in a wide range of scientific fields, and scientists who are not familiar with mathematics but have a basic knowledge of working in R can find many useful techniques for analysing their research data.'
-Maria Ivanchuk, International Society for Clinical Biostatistics, 71, 2021
