Normal Distribution

Normal distribution is a type of probability distribution that is widely used in statistics and mathematics. It is also known as a Gaussian distribution, after the German mathematician and physicist Carl Friedrich Gauss, who discovered it in the early 19th century. The normal distribution is one of the most important and commonly used distributions in many fields, such as physics, economics, biology, sociology, and psychology.

Normal distribution is characterized by a bell-shaped curve, which is symmetric around the mean. The mean is the average value of the data, and the standard deviation is the measure of spread of the data. Data points that are farther away from the mean are less likely to occur than those closer to the mean. The normal distribution is used to predict the probabilities of certain events occurring, such as the probability of a person scoring a particular number on a test, or the probability of a stock price moving in a certain direction.

Normal distribution is used in a variety of applications. It is used to predict the probability of outcomes in experimental studies, such as in medical research, where the normal distribution can be used to predict the probability of a certain outcome based on the number of participants in a study. It is also used in business and finance, where it can be used to predict the probability of a certain stock price moving in a certain direction. Additionally, normal distribution can be used to predict the probability of certain events occurring, such as the probability of a person winning a lottery.

Normal distribution is an important tool in statistics and mathematics, and it is used in many different fields. It is important to understand how normal distribution works and how it can be used to predict the probabilities of certain events occurring.

References

Ferguson, G. A. (2011). Normal distribution. In S. Kotz, C. J. Read, & D. L. Banks (Eds.), Encyclopedia of statistical sciences (Vol. 2, pp. 1130-1131). Wiley.

Kotz, S., & Read, C. J. (1992). Normal distribution and its applications. New York: Dekker.

Kotz, S., Read, C. J., & Banks, D. L. (Eds.). (2011). Encyclopedia of statistical sciences (Vol. 2). Wiley.

Papoulis, A. (2002). Probability, random variables, and stochastic processes (4th ed.). New York: McGraw-Hill.