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Multiple Linear Regression

Visualizing Results with Matplotlib

You’ve performed Multiple Linear Regression, and you also have the predictions in `y_predict`

. However, we don’t have insight into the data, yet. In this exercise, you’ll create a 2D scatterplot to see how the independent variables impact prices.

**How do you create 2D graphs?**

Graphs can be created using Matplotlib’s `pyplot`

module. Here is the code with inline comments explaining how to plot using Matplotlib’s `.scatter()`

:

```
# Create a scatter plot
plt.scatter(x, y, alpha=0.4)
# Create x-axis label and y-axis label
plt.xlabel("the x-axis label")
plt.ylabel("the y-axis label")
# Create a title
plt.title("title!")
# Show the plot
plt.show()
```

We want to create a scatterplot like this:

### Instructions

**1.**

Create a 2D scatter plot using `y_test`

and `y_predict`

.

The x-axis should represent actual rent prices and the y-axis should represent predicted rent prices.

**2.**

Add appropriate x-axis labels and y-axis labels, as well as a title.

**3.**

Show the plot using `plt.show()`

.