INTRODUCING DATA-DISTRIBUTIONS INTO POWERLIST 2025

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Distributions are a fundamental concept in statistics, helping us make sense of data and predict future trends. Whether its the bell-shaped curve of the normal distribution or the right-skew of the Poisson distribution, each type offers a unique lens through which we can view and understand our data.
A power law distribution has the property that large numbers are rare, but smaller numbers are more common. So it is more common for a person to make a small amount of money versus a large amount of money. The Pareto distribution is a continuous power law distribution that is based on the observations that Pareto made.
Common probability distributions include the binomial distribution, Poisson distribution, and uniform distribution. Certain types of probability distributions are used in hypothesis testing, including the standard normal distribution, the F distribution, and Students t distribution.
An example of a continuous distribution would be choosing people at random from a sample and recording their height. This is a continuous variable as values could be in the range [24, 107] inches.
A data distribution is a graphical representation of data that was collected from a sample or population. It is used to organize and disseminate large amounts of information in a way that is meaningful and simple for audiences to digest. For example: Figure 1 - Histogram example.
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The Normal Distribution, also known as the Gaussian distribution, represents symmetrical data around a central point (mean) with a characteristic bell-shaped curve. Many natural phenomena, like human height, weight, or test scores, follow a normal distribution.

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