Non-Normal Distributions

Non-normal distributions are types of data patterns where values don't follow the classic bell-shaped curve of a normal distribution. Instead, they can be skewed to one side, have multiple peaks, or follow irregular shapes. For example, income levels often have many low earners and fewer high earners, creating a right-skewed distribution. Recognizing non-normal distributions helps in understanding real-world phenomena that don’t fit the standard pattern, affecting how we analyze data and make predictions. Different statistical methods are often needed for these distributions to accurately interpret the underlying information.