Estimation of model parameters is an essential part in regression analysis. We do that by using the Ordinary Least Squares method
Multiple Linear Regression Analysis with Categorical Predictors is done using Indicator Variables. We have to clearly analyze all possible models and select the best fitting model.
We use indicator variables when we have categorical variables in the Regression Equation. They are also known as Dummy Variables.
Simple Linear Regression is used to model the relationship between one predictor variable and one response variable. This is called ‘linear because the said relationship can be expressed in the form of the equation ‘y = mx + x”. And it is called ‘Simple’ because only one Predictor Variable is involved.
What is Regression Analysis? Regression Analysis is a Statistical Technique used to investigate and model the relationship between variables. It helps to identify trends associated with data and quantify them. In regression analysis, there are 2 main types of variables. Predictor Variable (Independent Variable) and Dependent Variable (Response Variable). For example, let’s say we use