non-parametric statistics

Nonparametric statistics is a type of statistical analysis that does not rely on the assumption of a specific underlying distribution (such as the normal distribution), or any other specific assumptions about the population parameters (such as mean and variance). This is in contrast to parametric statistics, which make such assumptions about the population. In nonparametric statistics, a distribution may not be specified at all, or a distribution may be specified but its parameters, such as the mean and variance, are not assumed to have a known value or distribution in advance. In some cases, parameters may be generated from the data, such as the median. Nonparametric statistics can be used for descriptive statistics or statistical inference. Nonparametric tests are often used when the assumptions of parametric tests are evidently violated. Definitions The term "nonparametric statistics" has been defined imprecisely in the following two ways, among others: Applications and purpose Non-parametric methods are widely used for studying populations that have a ranked order (such as movie reviews receiving one to four "stars"). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in ordinal data.