# Normal Distribution

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## Definition of 'Normal Distribution'

In statistics, a normal distribution is a continuous probability distribution that is symmetric about the mean, showing a bell-shaped curve. The normal distribution is often used in statistics to represent real-world data, such as the distribution of human heights.

The normal distribution is defined by its mean and standard deviation. The mean is the average value of the data, and the standard deviation is a measure of how spread out the data is.

The normal distribution is a very important distribution in statistics because it is the basis for many statistical tests and procedures. For example, the t-test and the z-test are both based on the normal distribution.

The normal distribution is also used in many applications in finance, such as pricing options and valuing stocks.

In finance, the normal distribution is often used to model the returns of stocks and other investments. This is because the returns of stocks tend to follow a normal distribution over time.

The normal distribution can be used to make predictions about the future returns of stocks. For example, a financial analyst might use the normal distribution to estimate the probability that a stock will return a certain amount of money over a certain period of time.

The normal distribution is a powerful tool in finance, and it can be used to make a variety of predictions about the future. However, it is important to remember that the normal distribution is only a model, and it is not always accurate.

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