What Is a Normal Distribution?
A normal distribution, also known as a Gaussian distribution or bell curve, is a type of continuous probability distribution for a real-valued random variable. It is a symmetrical arrangement of a data set in which most values cluster in the center, at the mean, and then taper off symmetrically toward each extreme.
Section 2: Key Properties of a Bell Curve
The key properties of a normal distribution are its bell-like shape and its symmetry around the center. In a perfect normal distribution, the mean, median, and mode are all the same value. The spread of the curve is determined by its standard deviation, which measures how far the data points are from the mean.
Section 3: A Practical Example
A classic example of a normal distribution is the height of adult humans. Most people are of average height (the peak of the bell curve), while progressively fewer people are significantly taller or shorter. If you were to graph the heights of a large population, the data would form a bell shape.
Section 4: Why Is Normal Distribution Important?
The normal distribution is a fundamental concept in statistics because it appears in many natural and social phenomena. It is widely used in statistical inference, hypothesis testing, and constructing confidence intervals. Understanding it allows statisticians and researchers to make predictions and interpret data about a population.