Pearson’s correlation is a far-fetched mathematical calculation invented by Karl Pearson, the same man responsible for creating Standard Deviation in statistics. Karl was responsible for several mathematical discoveries and incredible results in the exact area. And Pearson’s correlation is an amazing formula for understanding more about how two variables behave.
Do you know what this calculation works for? Come and understand everything about Pearson’s correlation in our article!
What is Pearson’s correlation?
The Pearson correlation is a mathematical calculation created by Karl Pearson to identify the relationship between two quantities, which are variables.
Also called Pearson’s correlation coefficient, the calculation exists to identify the tension between two variables, which are continuous. In simple terms we can summarize the calculation of the Pearson coefficient as follows:
When the Pearson correlation coefficient between the two continuous quantities is 0, it means that there is no association between the two variables;
When the Pearson correlation coefficient between the two continuous quantities is positive, greater than >0, it means that the association between the two variables is positive. As one increases the other variable also increases;
When the Pearson correlation coefficient between the two continuous quantities is negative, less than <0, it means that the association between the two variables is negative. As one increases the other variable decreases, generating a situation that we call inversely proportional.
This is a summary enough to understand in a general way what is Pearson’s correlation and how its results work.
How is Pearson’s correlation calculated?
Pearson’s correlation calculation is quite complex, its formula can be summarized as follows:
This is the correlation formula. We can note the variables of the formula, which are distributed as follows:
- X = continuous variable number 1;
- Y = continuous variable number 2;
- ZX = standard deviation of variable X;
- ZY = standard deviation of variable Y;
- N = number of data.
The calculation, being quite complex, can only be done by good mathematicians and statisticians who know the subject well.
What is the meaning of Pearson’s correlation?
The Pearson correlation means the relationship that the two magnitudes have with each other. As already mentioned, the possible results in summary are ,0, +1 or -1.
When the result is +1 it means that the relationship between the two magnitudes is proportional, and -1 is when the result is inversely proportional. In the case of 0 it means that the calculation of the correlation cannot define what is the relationship between the two magnitudes, but in a concrete situation it cannot mean that there is no relationship between the two variables.
It just means that this relationship in the context of calculation is impossible to calculate or identify.
What are the advantages and disadvantages of Pearson’s correlation?
As with any calculation used in the area of statistics, there are advantages and disadvantages to calculating Pearson’s correlation. As an advantage, we can highlight the fact that the calculation does not depend on the result to be done, and also on the accuracy of the formula if the two magnitudes are large enough.
Among the disadvantages, however, can be pointed out the need for the two magnitudes to present a continuous quantitative level, and the lack of accuracy if there is little data.
But did you already know this elaborate calculation? The calculation of Pearson’s correlation coefficient is very advanced, but widely used in the discipline of statistics.