STOP Correlation vs Causation CONFUSION with SIMPLE Data Visualization

Why Scatter plot and Bubble chart are used? What is a Confounding Variable? In this video, we'll explore the power of scatter plot and bubble chart for data analysis, using Matplotlib Library in Python. Learn how to visualize relationships between variables helps avoid the common mistake of confusing correlation with causation. We'll walk you through creating a Python bubble chart with 3 variables using the MPG dataset from kaggle.com and show you how to interpret confounding variable to make smarter business decisions. Specifically, you'll discover: 00:00:42 Basic Data Visualization Concept of Scatter Plot along with Limitations 00:02:53 How to Enhance Scatter Plot using Bubble Charts using Matplotlib in Python 00:05:50 Confounding Variable Impact for Business Decision Making Understanding confounding variable is part of multivariate data analysis and you will know why correlation does not imply causation. In the end, the overall goal is to find hidden insights or better context when performing data analysis by integrating 3 variables into a scatter bubble chart using Python on Kaggle dataset in MPG. Plus, get a bonus tip on optimizing bubble chart sizes for accurate data visualization. #datavisualizationstorytelling #statisticsmultivariate #bubblecharttutorial Kaggle Dataset Link: https://www.kaggle.com/datasets/uciml/autompg-dataset My Linkedin Profile: https://id.linkedin.com/in/vincent-handara-89955919 Related Video: https://youtu.be/qERzS8fQb6Y?si=lRoOaX_hC9KNyLZE Keywords: python matplotlib tutorial for data analysis, bubble chart tutorial, matplotlib scatter plot tutorial confounding variable, Correlation vs Causation, data visualization storytelling, multivariate analysis, exploratory data analysis, data visualization for data science, kaggle tutorial python, statistics multivariate