Simple linear regression

In simple linear regression, we try to predict one variable in terms of a second variable called a predictor variable. The variable we are trying to predict is called the dependent variable and is denoted by y, and the independent variable is denoted by x. In simple linear regression, we assume a linear relationship between the dependent attribute and predictor attribute.

First we need to plot the data to understand the linear relationship between the dependent variable and independent variable. Here our, data consists of two variables:

• YPrice: Dependent variable

• XPrice: Predictor variable

In this case, we are trying to predict Yprice in terms of XPrice. StockXprice is the independent variable and StockYprice is the dependent variable. For every element of StockXprice, there is an element of StockYprice, which implies one-to-one mapping between elements of StockXprice and StockYprice.

A few lines of data used for the following analysis are displayed using the following...