**Regression model** predicts the relational ship between the **dependable variable** and **independent variable**. Regression model is helps to find the value of dependable variable based on the independent variable. The **simplest form** of regression model is **linear regression**.

Linear Regression is used to predict the relationship between the two quantitative variables to find the best fitted** linear line** is also called as **Regression line**. The variable we are predicting is called** criterion variable** as dependent variable(y-axis).The variable we are basing for our predicting is called **predicator variable** as independent variable.(x-axis).The simple linear regression equation is y=b*X+a

b= slope

a=Intercept

Here we going to understand the relationship between the Energy bill as dependent variables (x-axis)and average Temperature as independent variable (y-axis)

Energy bills(in $) Temperature(F)

26.96 78.5

25.5 70.5

35.07 61

51.31 54

58.47 51.5

The best line of fit is y = -1.20125x + 115.20286

The graph below for verification.

Thank you

Aarthy Nagarajan

## Comments