Korrelatsiooni kalkulaator

Arvuta Pearsoni korrelatsioonikordajat lineaarsete seoste mõõtmiseks

Both datasets must have the same number of values.

Tulemused

Sisesta väärtused ja klõpsa Arvuta, et näha tulemust.

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 1

\(\text{Study hours: } [2,3,4,5,6], \text{ Test scores: } [65,75,80,90,95] \rightarrow r = 0.99\)

Example 2

\(\text{Temperature: } [10,15,20,25,30], \text{ Ice cream sales: } [100,150,200,250,300]\)
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