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This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business.
Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel. A negative correlation indicates the extent to which one variable increases as the other decreases.
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What Is the Karl Pearson Correlation Analytical Technique?
The Karl Pearson Correlation measures the degree of linear relationship between two variables.
In order to better understand the application of the Karl Pearson Correlation technique, let’s look at a sample analysis showing a positive correlation among data points.
Like other forms of correlation analysis, the Karl Pearson method measures the strength of relationships between only two variables, without taking into consideration the fact that both these variables may be influenced by a third variable. For example, the sale of ice cream and the sale of cold drinks are related to weather conditions. They may show a positive correlation but they are not related to each other, but rather to the weather. Correlation analysis is applied only to numeric values, so if the data is not in numeric form, it must be converted. For example, survey responses like “Very dissatisfied.” “dissatisfied,” “neutral,” “satisfied,” “very satisfied,” etc., must be converted to numeric ranking (i.e., 1,2,3,4,5).
How Can the Karl Pearson Correlation Method Be Used to Target Enterprise Analytical Needs?
Let’s take a moment to look at a use case so that we might better understand the application of the Karl Pearson Correlation method of analysis.
Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders.
Input Data: The delinquency rate of each credit card customer and the monthly income of each credit card customer.
Business Benefit: The credit card manager can decide on individual credit limit eligibility based on the correlation coefficient value between income and delinquency rates.
Correlation analysis and the Karl Pearson Correlation method can be used to identify negative, positive, and neutral correlations between two data points (e.g., the relationship between the age of a consumer and the color of shirt they might purchase or the level of education of a consumer and the delivery mechanism they choose for news and information).