Data Science - Statistics Correlation vs. Causality

Correlation Does Not Imply Causality

Correlation measures the numerical relationship between two variables.

A high correlation coefficient (close to 1), does not mean that we can for sure conclude an actual relationship between two variables.

A classic example:

During the summer, the sale of ice cream at a beach increases
Simultaneously, drowning accidents also increase as well

Does this mean that increase of ice cream sale is a direct cause of increased drowning accidents?

The Beach Example in Python

Here, we constructed a fictional data set for you to try:

Example

import pandas as pd
import matplotlib.pyplot as plt

Drowning_Accident = [20,40,60,80,100,120,140,160,180,200]
Ice_Cream_Sale = [20,40,60,80,100,120,140,160,180,200]
Drowning = {"Drowning_Accident": [20,40,60,80,100,120,140,160,180,200],
"Ice_Cream_Sale": [20,40,60,80,100,120,140,160,180,200]}
Drowning = pd.DataFrame(data=Drowning)

Drowning.plot(x="Ice_Cream_Sale", y="Drowning_Accident", kind="scatter")
plt.show()

correlation_beach = Drowning.corr()
print(correlation_beach)

Try it Yourself »

Output: