Regression Analysis
Hope you all are doing well. In this blog we will discuss the theory part of Regression Analysis. In upcoming blog we will see the actual implementation. So, let’s get started.
What is Regression Analysis ?
Regression analysis is a predictive analysis which estimates the relationship between two or more variables. It focuses on the relationship between independent/predictors and dependent/target variables. For example house of the price dependents upon the various factors like size of the house etc. Here, house price is dependent/target variable and size of house is independent variable.
Need of Regression Analysis :
As we know now Regression analysis estimates the relationship between two or more variables. More specifically, regression analysis helps us understand how the typical value of dependent variable changes when any one of the independent variable is varied. There are many scenarios where we can not all the independent variables have the same affect on the dependent variable. Some has direct and positive affect and some have negative affect. For example salary of an individual have no effect on house price.
Benefits of Regression Analysis :
It indicates the strength of impact of multiple independent variables on a dependent variable and also helps us to determine which variables are most strong predictors of the dependent variable.
Types of Regression Technique :
Linear Regression : It establishes the relation between dependent/target (Y) variable and one or more independent/variable (X) by fitting best straight line(regression line).
Logistic Regression : It is used to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio level independent variables.
Polynomial Regression : A regression equation is called a polynomial if the power of independent variable is more than 1.
Ridge Regression : Ridge regression is suitable for analyzing data that suffers from multi-col-linearity.
I hope this will help to understand the basic of Regression Analysis. We will see the real implementation in upcoming blogs.
Stay tuned.
