Frequently used probability distributions in biostatistics

by | Mar 4, 2023 | Research

 

 

 

 

 

 

In this module, you have learned about two of the most frequently used probability distributions in biostatistics: the binomial and normal distributions. The binomial distribution and the normal distribution are similar in several ways. In fact, under certain conditions, the normal distribution is used to approximate the binomial. For your initial post, discuss the following three questions. Provide examples of data that follow each distribution to help illustrate your points.

What are the basic differences between the two distributions?
Under what circumstances do you think it works well to approximate the binomial using the normal, considering the differences?
Under what public health or medical circumstances would it be helpful to identify the probability of an event? Provide some real-life examples.

Sample Solution

The binomial and normal distributions are two of the most commonly used probability distributions in biostatistics. The binomial distribution describes a situation in which there are two possible outcomes, usually referred to as “success” or “failure”. The normal distribution is an approximation of the binomial distribution when the number of trials (n) is large.

Sample Solution

The binomial and normal distributions are two of the most commonly used probability distributions in biostatistics. The binomial distribution describes a situation in which there are two possible outcomes, usually referred to as “success” or “failure”. The normal distribution is an approximation of the binomial distribution when the number of trials (n) is large.

The basic difference between these two distributions is that the binomial is discrete and has two possible outcomes – success or failure; whereas the normal distribution is continuous with infinite possibilities for any outcome. Additionally, unlike the normal distribution, the probability associated with each outcome in a binomial distribution depends on n; therefore it can be defined by its mean (μ) and variance (σ2). Under certain conditions, it works well to approximate the binomial using the normal because they both have similar properties – meaning their means μs and variances σ2s relatively close!

 

In public health and medicine, understanding probabilities can be helpful in many circumstances such as determining likelihood of diagnosis given set symptoms testing results assessing risk factors specific diseases illnesses predicting/identifying phases treatments based individual patient conditions etcetera . For example if someone shows signs flu-like symptoms then healthcare provider could use data from previous cases determine what kind virus likely causing illness guide course treatment needed so person gets back healthy soonest possible time!

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