Question

What are the :

a) advantages of parametric tests

b) disadvantages of parametric tests

c) advantages of nonparametric tests

d) disadvantages of nonparametric tests

Answer 1

Answer a: Advantage of Parametric Tests:

1.  Parametric tests can provide trustworthy results with distributions that are skewed and nonnormal

2. Parametric tests can provide trustworthy results when the groups have different amounts of variability

3. Parametric tests have greater statistical power

4. One of the biggest and best advantages of using parametric tests is first of all that you don’t need much data that could be converted in some order or format of ranks.

5. One of the biggest advantages of parametric tests is that they give you real information regarding the population which is in terms of the confidence intervals as well as the parameters.

Answer b: Disadvantages of Parametric Tests:

1. Parametric tests are not valid when it comes to small data sets. The requirement that the populations are not still valid on the small sets of data, the requirement that the populations which are under study have the same kind of variance and the need for such variables are being tested and have been measured at the same scale of intervals.

2. Another disadvantage of parametric tests is that the size of the sample is always very big, something you will not find among non-parametric tests. That makes it a little difficult to carry out the whole test

3. Typical parametric tests will only be able to assess data that is continuous and the result will be affected by the outliers at the same time. The non-parametric tests may also handle the ordinal data, ranked data will not in any way be affected by the outliners.

4. Parametric Tests makes it very difficult to work with Non-Normal Data when no assumption of Normality can be made.

Answer c: Advantages of Non Parametric Tests

I) Non Parametric methods are readily comprehensible, very simple and easy to apply and do not require complicated sample theory.
(il) No assumption is made about the form of the frequency function of the parent population from which sampling is done.
(iii) No parametric technique will apply to the data which are mere classiflcalion (i.e., which are measured in nominal scale), whileNon Parametric methods exist to deal with such data.
(iy) Since me socio-economic data ~ not, in general, normally distributed. Non Parametric tests have found applications in Psychometry, Sociology and Educational Statistics.
(v) Non Parametric tests are available to deal with the data which are given in ranks or whose seemingly numerical scores have the strength of ranks.

Answer d: Disadvantages of Non-Parametric Methods

(i) N.P. tests can be used only if the measurements are nominal or ordinal. Even in that case, if a parametric test exists it is more powerful than the Non-Parametric test. In other words, if all the assumptions of a statistical model are satisfied by the data and if the measurements are of required strength, then the Non-Parametric tests are wasteful of time and data:
(ii) So far, no Non-Parametric methods exist for testing interactions in analysis of variance model unless special assumptions about the additivity of the model are made.
(iii) Non-Parametric tests are designed to test statistical hypothesis only and not for estimating the parameters.