Correlation:
Correlation is described as the analysis that informs users about the association or the absence of any relationship between any two variables ‘x’ and ‘y.’ The word correlation combines ‘Co’ (together) and relation (interaction/connection) in context to any two quantities. Correlation between two given variables exists when a unit change in any one variable gains a retaliation (in response) in the form of an equivalent change in the other variable. The answer can be either direct or indirect. Conversely, the two variables are said to be uncorrelated in case the movement in any one variable fails to generate any flow in the other variable, be it directly or indirectly. Correlation is, therefore, a statistical technique representing the strength of the connection between any given pairs of variables.
Regression:
A statistical technique based on the average mathematical relationship between two or more variables is known as regression, to estimate the change in the metric dependent variable due to the change in one or more independent variables. It plays an important role in many human activities since it is a powerful and flexible tool that is used to forecast past, present, or future events based on past or present events. For example, The future profit of a business can be estimated on the basis of past records.Differences Between Correlation and Regression
Differences:
- Correlation helps create and define a relationship between two variables, and regression, on the other hand, helps to find out how one variable affects another.
- The data shown in regression establishes a cause and effect pattern when change occurs in variables. When changes are in the same direction or opposite for both variables, for correlation here, the variables have a singular movement in any direction.
- The regression will give relation to understand the effects that x has on y to change and vice-versa. With proper correlation, x and y can be interchanged and obtained to get the same results.
- Correlation is based on a single statistical format or a data point, whereas regression is an entirely different aspect with an equation and is represented with a line.
- In correlation, x and y can be interchanged; in regression, it won’t be applicable.