What is a Pearson Coefficient?

The Pearson coefficient refers to a type of correlation coefficient in statistics representing the relationship between two variables measured on the same ratio scale or the same interval. The Pearson coefficient is an associations measure of strength between two continuous variables.

How Does the Pearson Coefficient Work?

To be able to find the Pearson coefficient, you have to place the two variables on a scatter plot. Also, to calculate the coefficient, some linearity must be present. If your scatter plot does not depict any similarity to a linear relationship, then it becomes useless. Note that the closer the similarity to the scatter plots straight line, the higher the associations strength.

Numerical Representation of Pearsons Coefficient

When representing the Pearson coefficient numerically, you should do it the same way you will do with a correlation coefficient in the linear regression (from -1 to +1). A value of +1 means that the result has a perfect positive relationship between two or additional variables. On the other hand, a -1 value means that there is a perfect negative relationship. A zero value means that there is no correlation.

How is the Pearson Coefficient used in Investment?

For those investors who want to diversify their portfolios, they can make use of the Pearson Coefficient to do that. Pearson coefficient can assist investors in putting together a portfolio based on the return parameters and risk when they want to calculate historical returns scatter plots between pairs of assets like:

• Equities-commodities
• Equities-bonds
• Bonds-real estate
• Large-cap equities
• Small-cap equities
• Debt-emerging market equities

However, it is worth noting that a Pearson coefficient measures correlation and not causation. If small-cap and large-cap equities happen to have 0.8 as a coefficient, it will be impossible to know the real cause of the associations relatively high strength.

Who was Karl Pearson?

Karl Pearson was an English academic and a creative contributor in both the mathematics and statistics fields. Karl Pearson was a renowned English academic, as well as a creative contributor both in the field of mathematics and statistics. He lived the year between1857 and 1936. Besides the eponymous coefficient, he is known for the concepts of p-value and chi-squared test, and many more. He is also the one that developed classification distributions and linear regression. He founded the Department of Applied Statistics at University College London in 1911.