ABSTRACT
Nonparametric statistics is easy and simple. A branch of statistical analysis, it does not rely upon large quantitative data as is the case with parametric statistics. Sometimes nonparametric techniques are called ranking tests or order tests. The essential differences between non parametric and para metric statistics are:
Nonparametric statistical inference does not assume that scores under examination come from a normally distributed population as does parametric statistics.
Nonparametric statistical inference does not rely upon scores from populations that have the same variance.
Nonparametric statistics tests use values of nominal and ordinal scales whereas parametric tests use truly numerical scores.
Nonparametric statistics tests can use classificatory (categorical) data that cannot be ordered.
