F-critical value is a particular value that we used to compare our f value to. While conducting the F test we obtain F statistics as an outcome. For determining whether the result of the f test is statistically significant the f statistic is compared with the F critical value. If the F statistic is larger than the F critical value then we assume that the result of the test is statistically significant.
This article focuses upon finding F critical value in Python. Before proceeding further we need Scipy library already installed in our system. You can install this library by using the below command on your terminal,
pip3 install scipy
Calculating F critical value in Python is a step by step process,
Step 1: Import the Scipy library.
The very first step is to import the Scipy library. It is used for scientific computation and uses NumPy internally.
Python3
# Importing library import scipy.stats |
Step 2: Define parameters.
To calculate F-Critical value we need these parameters: A significance level, Numerator degrees of freedom, Denominator degrees of freedom. As an example, we have assumed respective values,
significance level = 0.01, numerator degrees of freedom = 4, and denominator degrees of freedom = 6
Step 3: Calculate F-Critical value.
For calculating F-Critical value scipy.stats provide us scipy.stats.f.ppf() function using which we can calculate the F-Critical value. The syntax is given below,
Syntax:
scipy.stats.f.ppf(q, dfn, dfd)
Parameters:
q: It represents the significance level to be used
dfn: It represents the numerator degrees of freedom
dfd: It represents the denominator degrees of freedom
Return Type:
Returns the critical value from the F-distribution
Example:
Python3
# Importing library import scipy.stats # Determine the F critical value print(scipy.stats.f.ppf(q=1-.01, dfn=4, dfd=6)) |
Output:
F-Critical value
Hence, The F critical value for a significance level of 0.01, numerator degrees of freedom = 4, and denominator degrees of freedom = 6 is 9.148.
Bonus:
The alpha value is inversely proportional to the critical values. For example, consider the below program having the alpha value = 0.05, numerator degrees of freedom = 4, and denominator degree of freedom = 6 (the latter two are the same as the above-taken example).
Example:
Python3
# Importing library import scipy.stats # Determine the F critical value print(scipy.stats.f.ppf(q=1-.05, dfn=4, dfd=6)) |
Output:
F-Critical value
Hence, The F critical value for a significance level of 0.05, numerator degrees of freedom = 4, and denominator degrees of freedom = 6 is 4.533.
