Data Science -

Statistics Standard Deviation

Standard Deviation:

You can use Standard deviation to describes
how spread out the observations are.



if the observations are wide "spread",
a mathematical function will have
difficulties in predicting precise values
Standard deviation is a measure of uncertainty.
If the standard deviation is Low,
that means that most of the numbers are
close to the mean (average) value.

Note: that Standard Deviation is often represented
by the symbol Sigma: σ

To find the standard deviation of a variable,
you can use the std() function from Numpy.

Example
import numpy as np
std = np.std(full_health_data)
print(std)

Output

Coefficient of Variation

If you want to get an idea of how large the standard deviation is,
you can use coefficient of variation to find it out.
In Mathematics, the coefficient of variation is defined as:

Coefficient of Variation = Standard Deviation / Mean

To work this out, you can use python as follows:
Example
import numpy as np
cv = np.std(full_health_data) / np.mean(full_health_data)
print(cv)

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