Why Averages Become Normal 📈 | Central Limit Theorem Visualized

Why does the normal distribution appear everywhere in statistics? In this BitSize Stats video, we visually explain the Central Limit Theorem by starting with raw, non-normal distributions and repeatedly taking random samples. As we plot the sampling means, a surprising pattern emerges: the distribution of averages becomes normal, even when the original data is not. This video focuses on visual intuition, not heavy formulas. You’ll see how the sampling distribution of the mean forms a bell curve and why this idea is fundamental to statistics, data science, polling, medicine, experiments, and machine learning. If you’ve ever wondered why averages tend to look normal, or why the normal distribution shows up so often in real-world data, this visual explanation will make it click. Topics covered: • Central Limit Theorem • Sampling distribution of the mean • Normal distribution • Statistics intuition • Data science fundamentals #CentralLimitTheorem #Statistics #DataScience #Probability #NormalDistribution #SamplingDistribution #BitSizeStats