# Linear Regression – Data VisualiZation using Seaborn

deeplearning.org.uk – Linear Regression

### Linear Regression

In statistics “**Linear regression**” is an approach for modeling the relationship between an independent **quantitative** variable **x** and a dependent **quantitative** variable **y **. This is called “**simple linear regression**“.

In case there are multiple independent variables x1, x2, …, xk , then the approach is called “**multiple linear regression**“.

If the dependent variable y is **categorical **(and not quantitative), for example we examine if y exists or not (**1 or 0**), then the approach is different and it is called “**logistic linear regression**“. We are going to examine logistic regression later.

There are numerous free resources for linear regression on the web, I recommend to check youtube videos by Brandon Foltz.

### Data VisualiZation using Seaborn, Python’s library

We are going to see how easy it is to visualize linear regression using python’s library Seaborn.

Seaborn comes with a couple of datasets included. One of them is called “tips” and it contains data of tips, total_bill, gender of the customer, if they were smokers or not, etc.

Looking the data carefully, we can realise that there is a linear relationship between the “total_bill” and the “tip”: the higher the “total_bill”, the higher the “tip” is; the lower the “total_bil”, the lower the “tip”.

Let’s show this linear relationship using Seaborn:

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