Statistical Analysis & Correlation

Understanding Relationships Between Variables

Correlation measures how two variables move together:

• +1: Perfect positive correlation (both increase together)
• 0: No correlation
• -1: Perfect negative correlation (one increases, other decreases)

Calculate Correlation

# Pearson correlation (default) — linear relationships
df.corr()                    # all numeric columns
df['age'].corr(df['salary']) # between two columns

# Spearman correlation — rank-based, more robust
df.corr(method='spearman')

Interpreting Correlation Strength

Visualizing Correlation

corr_matrix = df.corr()
# Use Matplotlib heatmap to visualize

Important: Correlation ≠ Causation. Just because two variables correlate doesn't mean one causes the other.