There are many instances that companies make use of correlation analysis. This tool is useful for determining the relationship between two variables. A company may want to know the relationship between the total number of salespeople to the total number of sales or the price of gold to the current dollar rate. This method can be very beneficial to us considering that we have good understanding of what it really provides.
Correlation analysis is a set of statistical examination to find out mathematically if there is a significant relation between two or more groups of data coming from the same list of items or securities (for example, SAT scores and college achievement). The result of the analysis can give you an answer on whether the two variables are correlated or have a significant relationship.
The correlation examination is composed of computing a correlation coefficient from the two groups of data. The value of the correlation coefficient will always range from +1 to -1. Perfect positive correlation or +1 shows you that if the independent variable (example SAT scores) increases then the dependent variable (example college achievement) will also increase. The perfect negative correlation coefficient or -1 shows you that if the independent variable increases then the dependent variable decreases. No relationship between two variables is determined with a zero correlation.
A lot of people commit the mistake of relating correlation with cause and effect. It can only determine how or to what extent the two specified variables are related or associated with each other. The correlation coefficient only measures the extent of linear relationship among the two variables. In the end, your conclusion on the cause in effect must rely on your own analysis not on the method. Always remember that correlation is not causation.
For example, education and income is positively correlated but you won’t know for sure that one variable caused the other. There is a chance that higher income provides people the capability to constantly get education. There is also a chance that acquiring a lot of education can cause a person to earn a lot. Again, this method can only show us the relationship between variables and not the cause. We shouldn’t acquire our conclusion on the cause and effect in this method.
A good understanding on correlation analysis can be very beneficial. It can aid you understand whether expectations are on or off base. Having the knowledge on variables that have significant relationship can improve accuracy on forecasting which then reduce risk and increase success.