Example 1
\(\text{Study hours: } [2,3,4,5,6], \text{ Test scores: } [65,75,80,90,95] \rightarrow r = 0.99\)
Korrelations-Rechner
Berechnen Sie den Pearson-Korrelationskoeffizienten zur Messung linearer Beziehungen
Ergebnisse
Geben Sie Werte ein und klicken Sie auf Berechnen, um das Ergebnis zu sehen.
Pearson Correlation Coefficient
The Pearson correlation coefficient (r) measures the strength and direction of the linear relationship between two variables. It ranges from -1 to +1:
- r = +1: Perfect positive linear relationship
- r = -1: Perfect negative linear relationship
- r = 0: No linear relationship
- 0.7 ≤ |r| < 1: Strong correlation
- 0.5 ≤ |r| < 0.7: Moderate correlation
- 0.3 ≤ |r| < 0.5: Weak correlation
- |r| < 0.3: Very weak or no correlation
Important: Correlation does not imply causation. A high correlation between two variables does not mean that one causes the other. Always consider other factors and the context of your data.
\(r = \frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum(x_i - \bar{x})^2 \sum(y_i - \bar{y})^2}}, R^2 = r^2\)
Worked Examples
Example 2
\(\text{Temperature: } [10,15,20,25,30], \text{ Ice cream sales: } [100,150,200,250,300]\)