Free Binomial Probability Distribution Essay Example
Type of paper: Essay
Topic: Information, Distribution, Weight, Health, Population, Value, Birth, Education
Pages: 1
Words: 275
Published: 2020/12/20
Binomial Probability Distribution.
The peer-reviewed health article used identified is “Using Empirical Methods to Rank Counties on Population Health Measures”. The ranks utilize population data to establish the variation in health appraisal across all the United States counties. The study was published online by the University of Wisconsin Population Health Institute in August 2013.
Binomial distribution is the distribution that describes a random variable that models the number of successes say k, that are obtained in n trials. The binomial distribution above can be obtained by carrying out n successive Bernoulli trials.
Binomial distribution is used in this study to model the number of low birth weight babies. The data on low birth weight involved a census of all the live births recorded as well as the number of births in which the baby had a low weight. The event low birth could be assigned either success or failure, and the numbers recorded and then the binomial distribution is used to estimate the probabilities. The tool considers the variable weight of infant for live births, and assigns a success value to weight above 2500g and a failure value for weights below 2500g. The table indicates that 20% of live births had low infant weight.
A random number generator was used to generate predictive data that was based on posterior sample for the binomial distribution and the recorded population data. Comparison between the predictive data set and the original data was achieved through quantification of posterior predictive P-values. The null hypothesis is rejected if the calculated p-value is below this threshold value. Therefore, it can be concluded that the data observed differ from the data simulated.
Reference:
Athens, J. K., Catlin, B. B., Remington, P. L., & Gangnon, R. E. (2013). Using Empirical Bayes Methods to Rank Counties on Population Health Measures. Preventing Chronic Disease, 10, E129. doi:10.5888/PCD10.130028
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