How to Compute Confidence Intervals in Python for Data Analysis (Scipy & Numpy)

🧠 Don’t miss out! Get FREE access to my Skool community — packed with resources, tools, and support to help you with Data, Machine Learning, and AI Automations! 📈 https://www.skool.com/data-and-ai-automations-4579 Want to make reliable estimates from your data? In this step-by-step tutorial, you’ll learn how to compute confidence intervals using Python, NumPy, and SciPy—a must-have skill for data analysis, statistics, and research! 🚀 Hire me for Data Work: https://ryanandmattdatascience.com/data-freelancing/ 👨‍💻 Mentorships: https://ryanandmattdatascience.com/mentorship/ 📧 Email: [email protected] 🌐 Website & Blog: https://ryanandmattdatascience.com/ 🖥️ Discord: https://discord.com/invite/F7dxbvHUhg 📚 *Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan 📖 *SQL and Python Courses: https://datacamp.pxf.io/XYD7Qg 🍿 WATCH NEXT Statistics for Data Science Playlist: https://www.youtube.com/playlist?list=PLcQVY5V2UY4LF-eHg0tfTpWHhgpX9XF4S Kurtosis: https://youtu.be/wLhBOSaGvC0 Geometric Distribution: https://youtu.be/F8ylt-PUUjc Central Limit Theorem: https://youtu.be/1yt791iNABE In this video, we dive deep into confidence intervals using Python and walk through multiple practical examples with real-world data. Learn how to calculate confidence intervals at 90%, 95%, and 99% levels, understand the difference between confidence and probability, and discover what factors influence the width of your confidence intervals. We start with the fundamentals, explaining exactly what a confidence interval is and how to interpret it correctly. Then we move into Python code, using libraries like NumPy, SciPy, and Matplotlib to calculate and visualize confidence intervals for marathon running data. You'll see how to create forest plots and bar charts to display multiple confidence intervals, and learn how sample size, variability, and confidence level all affect your results. Whether you're working with means, proportions, or comparing multiple groups, this tutorial covers everything you need to know about confidence intervals in statistics. By the end, you'll understand how to calculate confidence intervals manually, plot them professionally, and interpret what they actually mean for your data analysis. Keywords: confidence intervals, Python statistics, data visualization, matplotlib, scipy, numpy, statistical analysis, data science TIMESTAMPS 00:00 Introduction to Confidence Intervals 01:12 What is a Confidence Interval? 02:38 Example Calculation - Marathon Long Run 03:52 Factors Influencing Interval Width 04:40 Multiple Confidence Intervals 05:49 Setting Up Python Code 07:32 Example 1: Marathon Long Run in Python 11:02 Calculating Confidence Intervals (90%, 95%, 99%) 13:02 Example 2: Visualizing Confidence Level vs Width 16:17 Creating the Width Comparison Plot 18:58 Example 3: Forest Plot with Multiple Groups 23:22 Building the Forest Plot 28:29 Analyzing the Forest Plot Results 30:35 Example 4: Bar Chart with Confidence Intervals 32:39 Final Thoughts and Recap OTHER SOCIALS: Ryan’s LinkedIn: https://www.linkedin.com/in/ryan-p-nolan/ Matt’s LinkedIn: https://www.linkedin.com/in/matt-payne-ceo/ Twitter/X: https://x.com/RyanMattDS Who is Ryan Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF. Who is Matt Matt is the founder of Width.ai, an AI and Machine Learning agency. Before starting his own company, he was a Machine Learning Engineer at Capital One. *This is an affiliate program. We receive a small portion of the final sale at no extra cost to you.