Korrelation (EN)

Concept

Correlation describes a statistical relationship between two variables where changes in one variable are associated with changes in another. However, it does not indicate whether one variable causes the other. Correlation is typically quantified by the correlation coefficient, which can take values between -1 and 1 and indicates the strength and direction of the relationship. Correlation is a necessary but not sufficient condition for causality.

Types of Correlation

graph LR     A[Positive Correlation] --> B[Value movements in same direction]     C[Negative Correlation] --> D[Value movements in opposite direction]     E[No Correlation] --> F[No recognizable relationship]     G[Correlation Coefficient] --> H[+1 to -1]     H --> I[+1 Perfect positive correlation]     H --> J[-1 Perfect negative correlation]     H --> K[0 No correlation] 

In Context

• Typically used together with regression, covariance, and scatter plots
• Related to: Causality, Covariance, Variance, Regression
• Example use: Investigating the relationship between study time and exam results