Simple linear regression is a statistical method that allows us to summarize and study relationships between two continuous variables where the output of variable is directly proportional to input. The variable which we will be predicting is called criterion variable which is along the Y axis and the variable which we are basing our predictions is known as predictor which is along the X axis. When there is single predictor variable that method is called simple linear regression method and when we have more than 1 predictor that model is called multiple linear regression method.

Statistical relation has lot of examples like height and weight, speed and petrol consumption, router bandwidth and router cpu relation, pizza size and price relation etc.

In the previous post, we have used the KNN neighbor algorithm to predict the values. In this post, we will be using the simple linear regression method to predict the pizza prices.

Before moving to the machine learning code, we need to first understand what equation of line is. The equation of line represents the relationship between the X and Y axis. Formula of finding equation of line is y = mx + c

C is Y intercept where the line meets the Y axis.