A normal distribution is a pattern that appears when data is spread around an average. Imagine measuring the heights of thousands of people. Most people will have heights close to the average, while very few will be extremely short or tall. When we plot these measurements on a graph, they often form a bell-shaped curve. The highest point represents the average, and the curve slopes downward on both sides. This happens because values near the average are more common than values far away from it. The mean determines the centre of the curve, while the standard deviation determines how wide or narrow it is. A smaller standard deviation means values cluster closely around the average. In a normal distribution, approximately 68% of values fall within one standard deviation of the mean, 95% within two, and 99.7% within three. This pattern helps statisticians understand data, estimate probabilities, and identify unusual observations. However, not every dataset follows a normal distribution...