<P><STRONG>Nonparametric Statistical Tests: A Computational Approach</STRONG> describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the diff
Nonparametric statistical tests : a computational approach
β Scribed by Markus Neuhauser
- Publisher
- Chapman & Hall/CRC
- Year
- 2011
- Tongue
- English
- Leaves
- 247
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Content: Introduction and Overview Nonparametric tests for the location problem Tests in case of heteroscedasticity Tests for the general alternative Ordered categorical and discrete data The conservativeness of permutation tests Further examples for the comparison of two groups One-sample tests and tests for paired data Tests for more than two groups Independence and correlation Stratified studies and combination of p-values Estimation and confidence intervals Appendix. Nonparametric tests in R References
π SIMILAR VOLUMES
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and
Bootstrapping, a computational nonparametric technique for "re-sampling," enables researchers to draw a conclusion about the characteristics of a population strictly from the existing sample rather than by making parametric assumptions about the estimator. Using real data examples from per capita pe
<p><b>ββ¦a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.Β It also deserves a place in libraries of all institutions where introductory statistics courses are taught." β</b><i><b>CHOICE</b><br /> <br /> </i></p> <p>ThisΒ <i>