How does regression analysis work?

Regression analysis is a statistical method used to analyze the relationship between variables. This method helps in understanding how the value of a dependent variable changes when one or more independent variables are varied.

Regression Models

Regression models are created using historical data to predict future outcomes and make informed decisions based on data analysis. There are various regression techniques, with two common types being:

1. Linear Regression:

In linear regression, a straight line is used to predict the relationship between variables. It assumes a linear relationship between the dependent and independent variables.

2. Multiple Regression:

Multiple regression involves more than one independent variable to predict the dependent variable’s outcome. It helps understand complex relationships between multiple factors.

Predicting Outcomes

Regression analysis predicts outcomes by fitting a line to the data points that minimizes the sum of squared errors. This line represents the best estimate of the relationship between variables.

Informed Decisions

By analyzing regression models, organizations can make informed decisions based on data insights. They can understand how different variables impact the outcome and use this knowledge to optimize processes or improve performance.