The correlation coefficient is used to indicate the relationship of two random variables. It provides a measure of the strength and direction of the correlation varying from -1 to +1. Positive values indicate that the two variables are positively correlated, meaning the two variables vary in the same direction. Negative values indicate that the two variables are negatively correlated , meaning the two variables vary in the contrary direction. Values close to +1 or -1 reveal the two variables are highly related.
A number of correlation methods are used for different situations. OriginPro supplies three mothods, which are Pearson R Correlation Coefficient, Spearman R Correlation Coefficient and Kendall (tau-b) Correlation Coefficient.
You can set the following features in OriginPro when performing correlation coefficient analysis.
- Determine which correlation types are used to compute the correlation coefficient
- Pearson: a parametric statistic, which requires normality is valid
- Spearman, Kendall: two non-parametric methods, which are used when the normality is violated or the variables are rank data.
- Determine whether to output Scatter Plots as well as Add Confidence Ellipse on the plots. Customers also can set the Confidence Level for Ellipse if the check box of Add Confidence Ellipse is checked.
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Further, you can decide where to output your report tables and whether to output the Results Log dialog.
The figure above illustrates an example of the relationship between a students height and weight.
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