A linear regression model is quite easy to interpret. The model is of the following form:
y=β0 + β1X1 + β2X2 + ... + βnXn
The significance of this model lies in the fact that one can easily interpret and understand the marginal changes and their consequences. For example, if the value of x0 increases by 1 unit, keeping other variables constant, the total increase in the value of y will be βi. Mathematically, the intercept term (β0) is the response when all the predictor terms are set to zero or not considered.