What is parametric testing?
What is parametric testing?
A parametric test is a hypothesis testing procedure based on the assumption that observed data are distributed according to some distributions of well-known form (e.g., normal, Bernoulli, and so on) up to some unknown parameter(s) on which we want to make inference (say the mean, or the success probability).
█ Cheap VPS | $1 VPS Hosting
█ Windows VPS Hosting | Windows with Remote Desktop
█ Cheap Dedicated Server | Free IPMI Setup
Hi Friends,
Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed. Non-parametric tests are “distribution-free” and, as such, can be used for non-Normal variables.
Parametric tests assume underlying statistical distributions in the data. Therefore, several conditions of validity must be met so that the result of a parametric test is reliable. For example, Student’s t-test for two independent samples is reliable only if each sample follows a normal distribution and if sample variances are homogeneous.
Parametric tests assume underlying statistical distributions in the data. Therefore, several conditions of validity must be met so that the result of a parametric test is reliable. For example, Student’s t-test for two independent samples is reliable only if each sample follows a normal distribution and if sample variances are homogeneous.
In the literal meaning of the terms, a parametric statistical test is one that makes assumptions about the parameters (defining properties) of the population distribution(s) from which one's data are drawn
Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed. Non-parametric tests are “distribution-free” and, as such, can be used for non-Normal variables.
A parametric test is a hypothesis testing procedure based on the assumption that observed data are distributed according to some distributions of well-known form (e.g., normal, Bernoulli, and so on) up to some unknown parameter(s) on which we want to make inference (say the mean, or the success probability).
Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed. Non-parametric tests are “distribution-free” and, as such, can be used for non-Normal variables.
|
Bookmarks