Correlation vs. Causation & Pearson r

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Interpret the Pearson correlation coefficient (-1 to +1) and avoid confusing correlation with causal relationships.

The Pearson Correlation Coefficient (r)

The correlation coefficient r measures the strength and direction of a linear relationship between two variables:

+1.0: Perfect positive linear correlation (as X rises, Y rises proportionally).

0.0: No linear relationship.

-1.0: Perfect negative correlation (as X rises, Y falls proportionally).

Computing Correlation Matrix in Python

Try It Yourself »

import pandas as pd

data = {
    'advertising': [100, 200, 300, 400, 500],
    'sales': [120, 230, 310, 420, 510],
    'complaints': [45, 30, 25, 12, 10]
}
df = pd.DataFrame(data)
print(df.corr())

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Test Yourself With Exercise

+15 XP

What does a Pearson correlation coefficient of -0.92 indicate?

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