Correlation and Regression Analysis

Correlation and Regression Analysis

1. Correlation and regression analyzes are often used by market researchers to study the relationship between two or more variables.

2. Correlation analysis measures the closeness of the relationship between two or more variables.

   • They are applied to the values ​​that two different variables take on each of the elements of a sample, and they express whether both variables vary at the same time, that is, if the values ​​of one are higher or lower, the higher or lower the values ​​are. from the other If the values ​​of both variables increase or decrease at the same time, their correlation is positive; On the other hand, if the values ​​of one variable increase when those of the other decrease, or vice versa, their correlation is negative. If the variables change independently of each other, there is no correlation between them.

3. regression analysis is used to derive an equation that relates the criterion variable to one or more predictor variables.

   • Linear regression analysis is used to predict the value of one variable based on the value of another. The variable you want to predict is called the dependent variable. The variable that you are using to predict the value of the other variable is called the independent variable.
     • The linear regression method can be performed in multiple programs and environments, such as:
       • such as: • Linear regression R • MATLAB Linear Regression • Sklearn linear regression • Python Linear Regression • Excel Linear Regression