Data Applied: Correlation
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The document discusses correlation and the Pearson product-moment correlation coefficient. It defines correlation as any statistical relationship between two or more random variables. The Pearson coefficient is the most common measure of dependence between two quantities, with a value between -1 and 1. It is calculated by dividing the covariance of the two variables by the product of their standard deviations. The document also provides steps for calculating correlation using Data Applied's web interface.
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Data Applied: Correlation
- 2. CorrelationIn statistics, correlation and dependence are any of a broad class of statistical relationships between two or more random variables or observed data valuesThe most familiar measure of dependence between two quantities is the Pearson product-moment correlation coefficient, or "Pearson's correlation." Data Applied also uses Pearson product-moment correlation coefficient as a measure of correlation
- 3. Pearson product-moment correlation coefficientIt is a value between +1 and −1 inclusiveIt is widely used in the sciences as a measure of the strength of linear dependence between two variablesPearson's correlation coefficient between two variables is defined as the covariance of the two variables divided by the product of their standard deviations:
- 4. CalculationFor a variable Xi where i varies from 1 to N by :mean (M)= summation (Xi)/Nstandard deviation (S) = (summation(Xi-M)^2/N)^(1/2)Substitute these values and get the correlation
- 5. Correlation using Data Applied’s web interface
- 6. Step 1: Selection of data
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