What is Linear Regression ???

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. The basic formula for a simple linear regression with one independent variable (x) and one dependent variable (y) is:

y = b0 + b1 * x

where:

• y is the dependent variable
• x is the independent variable
• b0 is the y-intercept (the value of y when x is 0)
• b1 is the coefficient that represents the slope of the line (the change in y per unit change in x)

In multiple linear regression, there are more than one independent variables, and the formula is:

y = b0 + b1 * x1 + b2 * x2 + ... + bn * xn

where:

• x1, x2, ..., xn are the independent variables
• b1, b2, ..., bn are the coefficients for each independent variable

The coefficients can be estimated using a variety of methods, such as the ordinary least squares (OLS) method, and can be used to make predictions about the dependent variable.