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In regression, we normally have one dependent variable and one or more independent variables.

Regression Definition – Why is it called regression? If we are supposed to find the relationship between two variables, we can apply regression analysis. This would also mean that a student who has a high CGPA, would also have a higher probability of getting a high GRE score.īut what if I ask, “The CGPA of the student is 8.32, what will be the GRE score of the student?“ Here, we see that there’s a linear relationship between CGPA and GRE score which means that as the CGPA increases, the GRE score also increases.

Now, if we are supposed to understand the relationship between these two variables, we can draw a scatter plot. All the GRE scores are listed in one column and the CGPAs are listed in another column.

We go ahead and collect the GRE scores and CGPAs of the students of this college. Your first task would be to collect the details of all the students. You are conducting a case study on a set of college students to understand if students with high CGPA also get a high GRE score. Let’s understand the concept of regression with this example. Independent Variable: These are factors that influence the analysis or target variable and provide us with information regarding the relationship of the variables with the target variable.Dependent Variable: This is the variable that we are trying to understand or forecast.The process that is adapted to perform regression analysis helps to understand which factors are important, which factors can be ignored, and how they are influencing each other.įor the regression analysis is be a successful method, we understand the following terms:

Regression analysis is a statistical method that helps us to analyze and understand the relationship between two or more variables of interest.