# Parametric Test Assignment

Words: 1074
Pages: 5

Assignment-4
Submitted By: Simran Arora
Ans.1
In research statistics, we have 2 categories of tests for the purpose of data analysis and interpretation- one group is based on means and the other group is based on medians. Based on the outcomes of these tests, we accept or reject the hypotheses. The tests which are based on means of the groups are called parametric tests and the tests which are based on medians of the groups are called as non-parametric tests. Let us discuss them in detail.
Parametric tests
Parametric tests are used when the population is normally distributed, i.e. a bell-shaped curve which is symmetrical about the mean and is spread according to the value of standard deviation. Parametric tests are useful when the scales of
Z-test: It is used to compare two population means when the variance is known and the sample size is large.
2. Independent/Unpaired t-test: It is used to compare the means of two unpaired and independent groups.
3. Paired t-Test: It is used to compare the means of two paired and related groups.
4. One-way ANOVA: It compares the means of three or more independent or unrelated groups.
5. Two-way ANOVA: It compares the mean differences between 2 groups to check whether there is any relation of 2 independent variables with the 1 dependent variable.

Non-Parametric Tests
These tests are in contrast with the parametric test. Non-parametric tests are used when certain assumptions of the focused population are uncertain. For example, in the case when the data is not normally distributed. It uses the median as the central measure. Non-parametrical tests are useful when the scales of measurement used are nominal or ordinal, i.e. the data is to be categorized or ordered in a particular rank-order. These tests may be used with data collected using interval and ratio scales as well but then it simply causes wastage of a large amount of data in such a case. Non-parametric tests have less number of assumptions and less severe as