In most statistics books there will often be a reference to two types of statistical techniques namely ‘parametric’ and ‘non-parametric’.
In this seminar we explore the difference between the two techniques and focus on why the distinction is important.
The word ‘parametric’ comes from ‘parameter’ or characteristic of a population. Tests such as t-test and ANOVA have assumptions about the shape of the population distribution that need to be met (i.e. normality) whereas non-parametric techniques are distribution-free because they do not make any assumptions about the distribution of the population. The advantages and disadvantage of non-parametric techniques will be examined.
Non-parametric techniques are ideal when you have ordinal (ranked) or nominal (categorical) scales. They are also useful when you have small sample sizes or when you have violated the assumptions of parametric techniques
Register for Statistics Seminar: Chi-square & non-parametric tests using your MYVU Portal login.
For more information about this session please email Researcher.Development@vu.edu.au