feedbackOne real life example where the data follows a normal distribution is adult human height. This means that if you measured the height of a large group of adults from the same country or similar background, you'd see that most people are close to the average height, with fewer people being very short or very tall. This kind of pattern makes a bell shaped curve, which is what a normal distribution looks like. It follows the empirical rule because studies have shown that height spreads out in a predictable way: About 68% of people are within one standard amount (called a "standard deviation") from the average height. About 95% are within two standard deviations. And almost all (99.7%) are within three. This is useful because when data is normally distributed, we can: Make predictions easily (like what percent of people are shorter or taller than a certain height) Use common statistical tools like z-scores and t-tests Spot anything unusual or way outside the norm (like extreme heights