Statistics

Parametric and Nonparametric tests

We rarely heard of nonparametric tests while reading standard statistical books. However there are some scenarios where they should be used instead of parametric tests. [1] has beautiful blog about it, I am putting just a summary from that.

 

Different Tests

Table below displays various tests, I have verified that all of these tests are available in python stats package.

tests_1

When to Use Parametric Tests

  • Parametric tests can perform well with skewed and nonnormal distributions
    • It is important to follow guidance in the sample size of data as shown in table below
  • Parametric tests can perform well when the spread/variance of each group is different
  • It has Statistical power

tests_2

Reasons to Use Nonparametric Tests

  • Your area of study is better represented by the median
    • Income distribution is skewed and median is more useful than mean
    • Few billionaires can boost up the mean significantly
  • You have a very small sample size
    • Even less than what is mentioned in table above
  • You have ordinal data, ranked data, or outliers that you can’t remove

 

 

References:

[1] : http://blog.minitab.com/blog/adventures-in-statistics-2/choosing-between-a-nonparametric-test-and-a-parametric-test