P-Values Explained Simply: Avoid These Common Mistakes (Python Example)

The p-value is one of the most misunderstood ideas in statistics. Students memorize it. Researchers misuse it. And many people interpret it completely wrong. In this video, I break down the p-value from first principles, without jargon, and without unnecessary formulas. By the end, you’ll understand what a p-value really means, what it does NOT mean, and how to interpret it correctly in real research. In this video, you’ll learn: • Why the p-value confuses so many people • The most common wrong definitions of p-value • The correct interpretation (in plain language) • A simple coin-flip analogy that makes it click • Why 0.05 became the standard cutoff • What p-values cannot tell you about your study • How to avoid the most common p-value mistakes This video is perfect for: • Statistics students • Data analysts and data scientists • Researchers and graduate students • Anyone who has ever used a p-value without fully understanding it If you’ve ever wondered “Do I really understand p-values?” — this video is for you.