Regression models: a concise tutorial with theory and real-life examples
In this tutorial, we will discuss seven regression models with their respective mathematical equations and real-life examples.
What is regression?
Regression is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. Sometimes, independent variables are also known as explanatory variables.
The goal of regression is to fit a line (or a more complex mathematical model) that best captures the underlying relationship between the variables.
Regression can be used to make predictions about the value of the dependent variable based on new values of the independent variables. For example, a regression can be used to predict the price of a house based on its square footage, number of bedrooms, location, etc.
How do we explain regression models mathematically?
At a high level, regression is a statistical technique for modeling the relationship between a dependent variable and one or more independent variables. The goal of regression is to fit a mathematical equation to the data that best captures the underlying relationship between the variables.
