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FUNDAMENTALS OF NONPARAMETRIC METHODS
| Content Provider | Scilit |
|---|---|
| Author | Sprent, Peter Smeeton, Nigel C. |
| Copyright Year | 2016 |
| Description | Parametric inference assumes observations are samples from populations with distributions belonging to a specified family. We pointed out in the previous chapter that for nonparametric inference we make only weaker assumptions such as one of symmetry, or where two or more populations are involved, that their distributions differ, if at all, only in some measure of location such as their medians. This calls for a new approach to hypothesis testing and estimation. Book Name: Applied Nonparametric Statistical Methods |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2009-0-02778-2&isbn=9780429184710&doi=10.1201/b15842-4&format=pdf |
| Ending Page | 53 |
| Page Count | 22 |
| Starting Page | 32 |
| DOI | 10.1201/b15842-4 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2016-04-19 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Applied Nonparametric Statistical Methods Cybernetical Science Hypothesis Testing Nonparametric Methods Parametric Inference New Approach Weaker Assumptions Previous Chapter Distributions Differ Inference Assumes |
| Content Type | Text |
| Resource Type | Chapter |
