In most of the real-life datasets, there are information on more than one variable. Normally, the values of two or more variables are collected for each of the respondents, patients, countries, industries, or whatever. For example, researchers may collect data on variables such as height and weight of newborn babies along with information on other variables such as gender, health condition, and type of birth. An obvious interest of researchers is to investigate if there is any relationship (or association) between any two variables. This may be helpful to relate the weight of babies with their height, that is, to check if taller babies are heavier or not.