About this document
Parametric vs Nonparametric Tests Explained by Aditya Jain is a document available to read on EtoBox.
The document discusses parametric and nonparametric statistical tests. Parametric tests require data that follows a normal distribution and makes assumptions about population parameters. Common parametric tests include t-tests, z-tests, and F-tests. Nonparametric tests do not require assumptions about the population and can be used with ordinal or nominal data. They are less powerful but more robust than parametric tests. Common nonparametric tests include chi-square, sign, Mann-Whitney U, runs, and Kruskal
- Author
- Aditya Jain
- Language
- EN