# Bell Curve Definition: Normal Distribution Meaning Example in Finance.

Bell Curve Definition: Normal Distribution. Who discovered normal distribution? The normal distribution was first discovered by De Moivre in 1733. He was able to show that the distribution of the sum of a large number of random variables is approximately normal. The distribution was later refined by Laplace in 1812. What is the slope of a bell curve? A bell curve is a type of probability curve in which data values are distributed in a symmetrical fashion around a central point, with a relatively small number of values occurring at the extremes. The most common type of bell curve is the normal distribution, which is used to model many real-world phenomena, such as height, weight, and IQ scores.

The slope of a bell curve is a measure of how steep the curve is. It is typically expressed as a percentage and is calculated by dividing the standard deviation by the mean. For a normal distribution, the slope is equal to 100%. What are the 4 properties of normal distribution? 1) The mean, median, and mode of a normal distribution are all equal.
2) The normal distribution is symmetric around the mean.
3) The standard deviation of a normal distribution is a measure of its spread, and is equal to the square root of its variance.
4) The normal distribution is a continuous distribution.

##### What is the use of normal distribution?

The normal distribution is a continuous probability distribution that is defined by its mean and standard deviation. The normal distribution is often used to model data that is evenly distributed around a mean, such as heights or test scores.

The normal distribution is a valuable tool for statisticians and data analysts because it allows them to make predictions about data that is normally distributed. For example, if a data set is normally distributed, the statistician can use the mean and standard deviation to predict how many data points will fall within a certain range.

The normal distribution is also used in hypothesis testing. In hypothesis testing, the null hypothesis is that the data follows a normal distribution. The alternative hypothesis is that the data does not follow a normal distribution. If the null hypothesis is rejected, it means that the data is not normally distributed. What is the meaning of normal distribution? A normal distribution is a distribution of a random variable that is symmetric about the mean and has a bell-shaped curve. The normal distribution is the most commonly occurring distribution in nature and is often referred to as the "bell curve." It is important to note that the normal distribution is only a theoretical distribution and is not always observed in real-world data.