# Hypergeometric And Negative Binomial Distribution

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Ajay Devgan says, “By getting into distribution and production, I have actually widened my base” (Distribution Quotes, 2016). Distributions are all around us in the fields of programming, medical, the sciences in many of today colleges. For me, distributions occurred in the aspect of programming, childhood and motherhood. As a single mother with a son, distribution appears in many activities, such as college and taking care of my child. As a student in Trine University, statistics class has many great concepts and applications, thus I will discuss distributions and variables.

Different statistics variables such as random, discrete, and expected are helpful in the study of statistics. These different types of distributions use these variables
HD is the exact number of “S” in a sample. Calculations were the earliest use; and I use the same example as above. According to scientists, “the representation H (x; n, M, N) is the proper way to show this distribution. In contrast, NBD is the amount of failures per each random trial, with successes being fixed. Today, measurement, counting, and data are some of the ways they are used. The number of students that a tutor helped to receive either a pass or fail is my example. Nb (x; r, p) represented the Negative Binomial …show more content…
Along my journey, I encountered the following distributions; Normal, Exponential and Gamma. Additional continuous distributions are Weibull, Lognormal, and Beta. Normal Distribution (ND) is the first discovered landmark. ND is the most common distribution with regard to the central limit theorem which defines the averages of the variables from independent distributions. Karl Friedrich Gauss discovered the Gaussian distribution, meanwhile James Dalton Bell discovered the Bell Curve. The Gaussian distribution and the bell curve are known names for the Normal distribution. Speaking of Normal Distribution, measurements were the earliest use, but today, height, weights, telling time, numerical numbers, and the sciences are practical uses. Random weight of pregnant women in the month of January is an excellent example and it can be represented as F (x; u,

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