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Explained variance

You saw that rent prices between Houston and Las Vegas are correlated. However, to what extent can the price change in one city explain the price change in another city? By computing R-squared you are able to precisely quantify this.

A NumPy array of rents has been loaded for Las Vegas (lasvegas_rents) and Houston (houston_rents), as well as the dates associated with each measurement. The packages pandas as pd, NumPy as np, Matplotlib as plt, and the stats package from SciPy have all been loaded for you.

This exercise is part of the course

Foundations of Inference in Python

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Exercise instructions

  • Compute the Pearson correlation coefficient between houston_rents and lasvegas_rents.
  • Print the square of the correlation coefficient.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Compute the correlation between Houston and Las Vegas
r, p_value = ____

# Print R-squared
____
Edit and Run Code