This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business.
What is the Karl Pearson Correlation Analytical Technique?
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. The Karl Pearson’s 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 measure 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, 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.
The Smarten approach to augmented analytics and modern business intelligence focuses on the business user and provides tools for Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist. Smarten Augmented Analytics tools include assisted predictive modeling, smart data visualization, self-serve data preparation, Clickless Analytics with natural language processing (NLP) for search analytics, Auto Insights, Key Influencer Analytics, and SnapShot monitoring and alerts. These tools are designed for business users with average skills and require no specialized knowledge of statistical analysis or support from IT or data scientists. Businesses can advance Citizen Data Scientist initiatives with in-person and online workshops and self-paced eLearning courses designed to introduce users and businesses to the concept, illustrate the benefits and provide introductory training on analytical concepts and the Citizen Data Scientist role.
The Smarten approach to data discovery is designed as an augmented analytics solution to serve business users. Smarten is a representative vendor in multiple Gartner reports including the Gartner Modern BI and Analytics Platform report and the Gartner Magic Quadrant for Business Intelligence and Analytics Platforms Report.
Original Post: What is Karl Pearson Correlation Analysis and How Can it be Used for Enterprise Analysis Needs?Share