Question

Explain the difference between parametric Vs non parametric methods. Give examples to explain to your answer. Please provide a detailed answer.

Answer 1

Most ,of the statistical tests have the following two features in common:
(I) The form of the frequency function, of the parent population from which the samples have been drawn is assumed to be known, and

(ii) They were concerned with testing statistical hypothesis about the parameters of this frequency function or estimating its parameters.
For example, almost all the exact (small) sample tests of significance are based on the fundamental assumption that the parent population is normal and are concerned with testing or estimating the means and. variances of these populations. Such tests, which deal with the parameters of the population are known as Parametric Tests.

Thus, a parametric statistical Methods specifies certain conditions about the parameters of the population from which the samples are drawn.

For example,

There are many parametric methods available some of them are:

• Confidence interval used for – population mean along with known standard deviation.
• The confidence interval is used for – population means along with the unknown standard deviation.
• The confidence interval for population variance.
• The confidence interval for the difference of two means, with unknown standard deviation.

On the other hand, a Non-parametric (N.P.) Methods does not depend on the particular form of the basic frequency function from which the samples are drawn.

In other words, non-parametric Methods does not make any assumption regarding the form of the population.

There are many nonparametric methods are available today but some of them are –

• Spearman correlation test
• Sign test for population means
• U-test for two independent means