What is Linear Regression? Linear regression is a statistical modelling technique used to establish a relationship between a dependent variable and one or more independent variables. It assumes a linear relationship between the variables and aims to find the best-fit line that minimizes the difference between the predicted values and the actual observed values. In simple linear regression, there is one dependent variable and one independent variable. The relationship between the variables can be represented by a straight-line equation: Y = mX + c Where: Y represents the dependent variable (the variable we want to predict/ Target variable), X represents the independent variable (the variable used to predict the dependent variable/ Predictor variable), m represents the slope of the line (the change in y for a unit change in x), c represents the y-intercept (the value of y when x is 0). Source: javatpoint The Objective of Linear Regression: The goal of linear regression is to estimate the...
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