## Step by Step Discussion and Workout with Examples, Implementation manually and in R

A linear relationship between two variables is very common. So, a lot of mathematical and statistical models have been developed to use this phenomenon and extract more information about the data. This article will explain the very popular methods in statistics Simple Linear Regression (SLR).

## This Article Covers:

Development of a Simple Linear Regression model

Assessment of how good the model fits

Hypothesis test using ANOVA table

That’s a lot of material to learn in one day if you are reading this to learn. All the topics will be covered with a working example. Please work on the example by yourself to understand it well.

Developing the SLR model should not be too hard. It’s pretty straight forward. Simply use the formulas and find your model or use the software. Both are straightforward.

The assessment and the hypothesis testing part may be confusing if you are totally new to it. You may have to go over it a few times slowly. I will try to be precise and to the point.

## Simple Linear Regression(SLR)

When linear relation is observed between two quantitative variables, Simple Linear Regression can be used to take explanations and assessments of that data further. Here is an example of a linear relationship between two variables: