Here you can calculate a correlation analysis directly online. Just try it with the sample data. If you want to calculate the correlation for your own data, just copy it into the table above.
The results of the correlation analysis are clearly presented. At the top you can read the null hypothesis and the alternative hypothesis, then the valid cases and finally the calculated correlation coefficient. For the correlation coefficient you get the p-value. Finally, a scatter plot of the data is displayed.
Do you want to characterize the linear relationship between your variables or how the individual characteristics relate to each other? Then you have come to the right place for correlation analysis.
Here you get the linear relationship (direction and strength) of two or more variables. Select at least two metric variables and DATAtab will give you the appropriate regression coefficient.
Are you interested in the association of your ordinally scaled variables? Then select at least two ordinal variables and DATAtab will show you the strength and direction of the characteristic relationship.
Pearson Correlation Coefficient Calculator
Pearson's correlation coefficient measures the strength and direction of the relationship between two or more variables. Whether you want to calculate the Pearson Correlation or Spearman Correlation just add your data to the table above.
For the calculation of the pearson correlation, the following assumptions must be met:
- The data must have metric Scale of measurement
- The data should be normally distributed
- The relationship should be linear
- There should be no outliers
Furthermore, the covariance is also output. With the covariance you get a non-standardised measure of the correlation. In contrast, the correlation is normalised from -1 to +1.
Point-Biserial Correlation Calculator
Of course, you can also calculate the point biserial correlation online, just select a metric variable and a nominal variable with two values.
With the point biserial correlation you can measure the correlation between two variables if one of the variables is dichotomous. For example, you might be interested in whether there is a correlation between learning ability between children who do not have a TV and children who have a TV in their room. Learning ability would then be the metric variable and having a TV in the child's room would be the dichotomous variable.
DATAtab is also available in German, French and Spanish. Visit the Korrelation Rechner on the German page, the Calculateur de corrélation on the French page or the Calculadora de correlación on the Spanish page