Normality Test

A normality test is a statistical way to check if a set of data follows a bell-shaped distribution called the normal distribution. This is important because many statistical methods rely on data being normally distributed. The test examines the data’s shape, skewness, and other characteristics to determine if it aligns with a normal pattern. If the data is normal, it means it has a symmetrical distribution around the average, with most values near the center. Understanding this helps in choosing the right analysis methods and ensuring accurate results in research and decision-making.