There
are various statistical techniques for analysing data. To choose an appropriate
technique of statistical analysis in the challenging task to a research worker.
It has two main functions:

**1.**Interpretation of results, and

**2.**Presentation of data.

The
major types of tests are employed for analysing data so as to interpret the
results. There are:

(A)
Parametric statistics or tests, and

(B)
Non-parametric statistics or tests.

A
researcher has to select either of these approaches for analysing his own
research data. The

following
are the criteria for choosing an appropriate statistical approach.

**(A) Considerations for Parametric Statistics**

This
type of statistical analysis may be employed effectively in the following
conditions:

**1**. Probability or representative sample has been employed in the investigation.

**2**. Variables of the study can be qualified at interval scale.

**3**. Specific assumptions are fulfilled. The obtained data are normally distributed or not free distribution.

**4**. The population of the study has been clearly defined.

**5**. Objectives of the research study.

**Under this approach the following statistical techniques are employed :**

**(**To study the descriptive relationship of two or more variables:

*a*)*a*1 – Pearson’s product moment method of correlation (two variables)

*a*2 – Multiple correlation (more than two variables)

*a*3 – Partial correlation (more than two variables)

*a*4 – Factor analysis-extracting factors or estimating psychological or factorial validity of tests.

**(**To analyse the functional relationship of the variables:

*b*)*b*1 – Main effect of two treatments ‘

*t*’ test

*b*2 – Main effect of more than two treatments

*F*-test

*b*3 – Interaction effect of two or more variables-Two or more ways analysis variance techniques

*b*4 – Gain or loss of more than two treatments-Analysis of covariance and correlated ‘

*t*’ test.

**(B) Considerations for Non-parameteric Statistics**

This
type of statistical analysis may be used effectively in the following
situations:

**1**. When non-probability sample is selected in the research study.

**2**. The variables of the study are quantified at any level of measurement, mainly, nominal and ordinal scale. It may be in the discrete form.

**3**. No assumption is required for this approach.

**4**. Free distribution of data, may be skewed or may be normally distributed.

**5**. Objectives of the study.

**In this approach the following statistical techniques are generally used :**

**(**To study the relationship of two or more variables:

*a*)*a*1 – Spearman Rho correlation in small sample not in large sample for two variables. Data are available at ordinal or internal scale.

*a*2 –

*x*2 and contingency correlation. It is used when two or more variables are taken. The data may be nominal or ordinal scale or interval scale.

*a*3 – Analysis variance.

**(**To analyse the difference between two or more groups:

*b*)*b*1 – Median test for small test.

*b*2 –

*x*2 test for large sample also for small sample.

*b*3 – Run test and

*U*-test when data are on ordinal scale.

*b*4 – Sign test.

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