Question

When we create an array of values and calculate the standard deviation of the array in R (using sd() function) and Python (using std() function from NumPy package.), think and give an explanation why the results are different

Answer 1

This can be illustrated with an example.

R code pasted below for finding standard deviation

a<-c(10,5,30,20,80,76,38)
sd(a)
Output Screen

Python code pasted below for finding standard deviation

import numpy as np
a=np.array([10,5,30,20,80,76,38])
print(a.std())

Python Code in IDLE pasted

Output Screen

The reason we are getting different results is because of the way by which the standard deviation/variance is calculated. R calculates denominator with  N-1, while numpy calculates denominator with N. We will get a numpy result equal to the R result by using a.std(ddof=1), which tells numpy to use N-1 as the denominator when calculating the variance.

Python code pasted below for finding standard deviation

import numpy as np
a=np.array([10,5,30,20,80,76,38])
print(a.std(ddof=1))

Python Code in IDLE pasted

Output Screen

So now the output of both R and Python numpy are the same.