Phase 4: Exploratory Data Analysis · ~30 minutes · Python · pandas

Correlation Is Not the Whole Story

Bedrooms and bathrooms correlate at 0.88 in real Airbnb data. That number alone can't tell you whether one drives the other, or whether both are just symptoms of 'this is a bigger house.'

Hiring signal: Treats a strong correlation as a reason to look for a confounding variable, not as evidence of a direct causal relationship

What you will learn

Compute correlations across a real dataset's numeric columns
Propose a plausible confounding variable for a strong observed correlation
Test a confounding explanation using partial correlation
Identify what additional evidence a correlation would need before supporting a causal claim

Introduction

Type: Learn Languages: Python, pandas Prerequisites: Lesson 02 (Outliers and Data Quality) Time: ~30 minutes

Objective

Learning objectives

Compute correlations across a real dataset's numeric columns
Propose a plausible confounding variable for a strong observed correlation
Test a confounding explanation using partial correlation
Identify what additional evidence a correlation would need before supporting a causal claim

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

Create a free account to unlock Phase 0 and Phase 1 of every course — no credit card.