Any dataset that we want to analyze will have different fields (that is, columns) of multiple observations (that is, variables) representing different facts. The columns of a dataset are, most probably, related to one another because they are collected from the same event. One field of record may or may not affect the value of another field. To examine the type of relationships these columns have and to analyze the causes and effects between them, we have to work to find the dependencies that exist among variables. The strength of such a relationship between two fields of a dataset is called correlation, which is represented by a numerical value between -1 and 1.
In other words, the statistical technique that examines the relationship and explains whether, and how strongly, pairs of variables are related to one another is known as correlation. Correlation...
