Understanding
Correlation
Dr. Ajay Kumar Koli, PhD | SARA Institute of Data Science, India
Correlation
Correlation measures the strength and direction of the relationship between two variables.
Types of Correlations
Values range from -1 to +1.
+1: Perfect positive correlation (as one variable increases, so does the other).
-1: Perfect negative correlation (as one variable increases, the other decreases).
0: No linear relationship.
Why Correlation?
Understand relationships between variables.
Identify patterns and dependencies.
Inform decision-making and further analysis (e.g., regression).
Limitations of Correlations
Correlation does not imply causation.
Sensitive to outliers.
Only measures linear relationships.
Practice Correlation
| Correlation Type | Description |
|---|---|
| Positive Correlation | Variables increase together. |
| Negative Correlation | One variable increases, the other decreases. |
| Zero Correlation | No relationship between the variables. |
| Perfect Positive Correlation | Variables move together perfectly in the same direction. |
| Perfect Negative Correlation | Variables move together perfectly in opposite directions. |
| Non-Linear Correlation | Relationship is non-linear. |
Understanding Correlation Dr. Ajay Kumar Koli, PhD | SARA Institute of Data Science, India