Correlation analysis – Is your business using it right?
“One of the first things taught in introductory statistics textbooks is that correlation is not causation. It is also one of the first things forgotten” – Thomas Sowell
Correlation is a very powerful statistic device as it can tell us the degree of relationship between two variables. It is a statistical tool used to measure a relationship between two variables and how strong/weak the relationship may be. It can be used for spotting patterns within datasets. This particular analysis is helpful in determining the possible connections between variables. But it has to be clearly understood that correlation does not imply causation. Just because two variables have a close relation does not imply that one is responsible for the other. So to cut it short it is a test of how things are related. Having knowledge of the relationship between variables also gives us insight into future predictions of behavioural patterns.
Since correlation analysis spots patterns and strength of variables, we can infer that positive correlation implies that both variables increase in relation to each other whereas a negative correlation describes an inversely proportional relationship viz increase in one variable results in the other variable decreasing. Any score between 0.5 to 1 indicates a positive relationship whereas any score between -0.5 to -1 indicate a negative relationship. A score of 0 is an indicator of no relationship existing between the variables.
Types of Correlation
· Pearson Correlation – It is a widely used statistic to measure the degree of relationship between linearly related variables
· Kendell Rank Correlation – A non-parametric test that measures the strength of dependence between two variables
· Spearman Correlation – A non-parametric test that can test the association between variables
· Point-Biserial Correlation – It is used to measure the strength and direction of the association that exists between one continuous variable and one dichotomous variable
Uses of Correlation
· Used as a Projection Tool – Predicting the future based on current relationship status is one of the fundamental functions of correlation.
· Helpful in making direction change – In the case of inversely proportional relationship, helping to predict such inverse relation will help companies anticipate and avoid losses
· Advantageous for measuring performance – Identifying patterns help identify efficiencies in business. Patterns that show increase in cost can help reduce cost and patterns that signify improved efficiency in employee behaviour can be used to motivate employee behaviour
· Useful in Data Mining and Patterns – Use of existing data which is substantial in business can help monitor these patterns that can help business use it to leverage its position. This can help in better management, customer retention and improved operations.
Correlation describes the strength and direction of an association between variables. Not just marketers or producers, correlation can be used in everyday lives as the help track Key performance indicators. They can be used to reveal insights and interdependencies. Correlation help estimate the value of dependency of variables which can help garner actionable insights and they are the starting point of further investigation or deeper insights.
“If there is any correlation between the intellectual and the wise, it is likely that intellectuals have less wisdom than those of much lesser academic credentials – H. Melvin James”
Author – Benila Jacob, Mark John