Univariate Linear Regression

Univariate Linear Regression

In Univariate Linear Regression, we have one independent variable $x$ which we use to predict a dependent variable $y$.

We will be using the Tips Dataset from Seaborn’s Datasets to illustrate theoretical concepts.

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We will be using the following columns from the dataset for Univariate Analysis.

• Total_bill: It is the total bill of food served.

• Tip: It is the tip given on the cost of food.

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Goal of Univariate Linear Regression: The goal is to predict the “tip” given on a “total_bill”. The regression model constructs an equation to do so.

If we plot the scatter plot between the independent variable (total_bill) and dependent variable (tip), we will get the plot below.

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• We can see that the points in the scatter plot are mostly scattered along the diagonal.

• This is an indication that there can be some positive correlation between the total_bill and tip. This will be fruitful in modeling.

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Working

The univariate Linear Regression model comes up with the following equation of the straight line.

$\hat{y} = w_0 + w_1 * x$

Or

$tip\mathrm{\_}predicte$ ...