# Differentiate Between Parametric And Nonparametric Statistics Pdf

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In terms of selecting a statistical test, the most important question is "what is the main study hypothesis?

First of all, it is better to know each of them, then I want to elaborate to find the majors differences between both of them, in details. Indeed, inferential statistical procedures generally fall into two possible categorizations: parametric and non-parametric. 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, while a non-parametric test is one that makes no such assumptions. In this strict sense, "non-parametric" is essentially a null category, since virtually all statistical tests assume one thing or another about the properties of the source population s.

## Difference Between Parametric and Nonparametric Test

Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It only takes a minute to sign up. I've been doing a research on the subject, spoiler alert: I'm a noob on this. So far, I've been able to find lots of information about the differences between the two, but nothing about the similarities, except for this:. I've done my research as best as my abilities and understanding of the subject have allowed me to , I've searched on the site, I've found similarly written questions and getting answered without any issues , I've read the tour and help pages, so I'd love a heads up so I can keep up the quality of the content on the StackExchange sites.

Parametric Methods The basic idea behind the parametric method is that there is a set of fixed parameters that uses to determine a probability model that is used in Machine Learning as well. Parametric methods are those methods for which we priory knows that the population is normal, or if not then we can easily approximate it using a normal distribution which is possible by invoking the Central Limit Theorem. Parameters for using the normal distribution is —. Eventually, the classification of a method to be parametric is completely depends on the presumptions that are made about a population. There are many parametric methods available some of them are:. Nonparametric Methods In Non-Parametric methods, there is no need to make any assumption of parameters for the given population or the population we are studying. Here there is no fixed set of parameters are available, and also there is no distribution normal distribution, etc.

The three modules on hypothesis testing presented a number of tests of hypothesis for continuous, dichotomous and discrete outcomes. Tests for continuous outcomes focused on comparing means, while tests for dichotomous and discrete outcomes focused on comparing proportions. All of the tests presented in the modules on hypothesis testing are called parametric tests and are based on certain assumptions. For example, when running tests of hypothesis for means of continuous outcomes, all parametric tests assume that the outcome is approximately normally distributed in the population. This does not mean that the data in the observed sample follows a normal distribution, but rather that the outcome follows a normal distribution in the full population which is not observed.

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Need a hand? All the help you want just a few clicks away. Therefore, several conditions of validity must be met so that the result of a parametric test is reliable. They can thus be applied even if parametric conditions of validity are not met. Parametric tests often have nonparametric equivalents. You will find different parametric tests with their equivalents when they exist in this grid.

In the literal meaning of the terms, a parametric statistical test is one that makes assumptions about the parameters (defining properties) of the population.

Social researchers often construct a hypothesis, in which they assume that a certain generalized rule can be applied to a population. They test this hypothesis by using tests that can be either parametric or nonparametric. Parametric tests are usually more common and are studied much earlier as the standard tests used when performing research. You then conduct a test and gather data that you then analyze statistically.

Mesquita, Sulin Tao, Triphonia J. Box , Kampala, Uganda. Box , Dar-es-Salaam, Tanzania. Numerical models are presently applied in many fields for simulation and prediction, operation, or research.

#### What is a Parametric Test?

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## Winquaberntem1975

tmeastafrica.org › Maths › Maths Difference Between.

## Morgan L.

Parametric tests assume underlying statistical distributions in the data. 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. Nonparametric tests do not rely on any distribution.