An essay on probability distribution is based on the outcomes of experiments and the probabilities of their occurrence. This form of statistics essay is based on variables, discrete or continuous. In the case of a discrete variable, a probability can be easily assigned to each of the possible values. Essays on probability distributions are used in broad applications. Essays on probability distribution have been used in both theoretical and practical applications, especially in the insurance sector by actuaries.

The need for simulation studies that come with random numbers generated from the use of specific probability distributions is at best inevitable. When computing within this type of statistics essay it is of significance to note that probability functions may mean both discrete and continuous distributions. Probability distributions can either be tabulated or the distribution functions can be used to get a certain probability in an outcome.

Essays on probability distribution have been extensively used in statistical data analysis since most of the data may involve assumptions. When doing an analysis of the data, a choice between the methods that generate distributional assumptions and those that make no assumptions about the distributions is always a given. Probability density functions bear information that is used in various disciplines of logic. It has been assumed that probability functions are for continuous distribution, while in reality, a density function will contain random functions if the distribution is discrete. Probability distributions should be repeated for consistency and accuracy purposes. For example, the relative frequency of the events should be noted. The ideal experiment that shows probability distribution is the tossing of a coin which should be repeated several times since there are several possible results that can be achieved with the same experiment.

## Probability Distributions essay example

Probability distribution is a very laden statistical term from which various other elements in statistical analysis emanate. Most students usually cringe at the mere mention of it. The However, probability distribution is a relatively easy concept as compared to most other statistical and mathematical concepts. Probability distribution refers to a mathematical function that describes a random variable that has the probability of taking certain values. It is also referred to as probability mass or probability density.

It is common knowledge that probability distribution is divided into two distinct probability distributions. These are discrete probability distribution and continuous probability distribution (Gerald 2006). It is widely known that many students are unable to fully grasp the differences in the two forms of probability distributions even though such differences are simple and well articulated in most literary texts concerning probability.

In discrete probability distributions one can easily assign a probability to each given value. A simple case in point is the probability of getting a given number on the roll of a die. For any given number that probability is always one sixth. When two dies are rolled then the probability of getting any given number increases to one third.

Whereas in continuous probability distribution mostly found in measurements the probability of obtaining a certain figure may actually be zero. For example, the probability of getting three and three quarter’s kilogram or maize may be zero. This means that even though you can get maize of that given kilogram there is also a good chance that you might not get it.

This is fundamentally different from discrete distribution because in the roll of a dice there is never a probability of zero. It does not arise (Marcus 2001). There is always a one out of six chance that you will get the number you desire.