Correlation coefficient is the first statistical index designed by statistician karl pearson, and it is the quantity to study the linear correlation between variables. Generally, it is represented by the letter R. Because of different research objects, there are many definitions of correlation coefficient, and Pearson correlation coefficient is the most commonly used one.

Correlation table and graph can reflect the relationship between two variables and their correlation direction, but they can't accurately show the degree of correlation between two variables.

Correlation coefficient is a statistical index reflecting the close correlation between variables. The correlation coefficient is calculated according to the product-difference method, which is also based on the deviation between two variables and their respective average values, and the correlation degree between the two variables is reflected by multiplying the two deviations; The linear single correlation coefficient is studied emphatically.

Extended data:

The range of correlation coefficient is [- 1, 1]. If the scatter point is to the upper right, r is greater than zero and less than one, the denser it is, the closer it is to a straight line, and the closer it is to1; On the other hand, if the scatter point is at the lower left, r is less than zero and greater than minus one, and the denser it is, the closer it is to a straight line, and the closer it is to-1. Generally speaking, R has a strong positive correlation between 0.75 and 1, and a strong negative correlation between -0.75 and-1.

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