The Normal Distribution
Initial Post Instructions
Many variables in medicine follow a normal distribution where there are approximately an equal number of values below the mean as above the mean. Describe two variables that you work with that would probably follow a normal distribution. Also note which of the two variables would be likely to have a larger standard deviation and why.
The Normal Distribution
Statistical data is essential to the healthcare providers, and statistics knowledge similarly is necessary not just for research but also for comprehending and interpreting appropriate information to the medical science practice (Holmes, lllowsky & Dean, 2017). A vital element of the statistical data usually is normality which is mainly characterized by distribution. Getting dipper into probability distribution, it is asymmetric about mean, revealing that data near mean is more common in the occurrence than the data far from mean. In a graph, the normal distribution resembles a symmetrical bell curve. Half the data usually falls to the left of mean, whereas half of the data falls to right.
Two significant variables I work with that would probably follow normal distribution are systolic blood pressure and height. According to Wadhwani, Siddiqui & Sharma (2018), the systolic blood pressure variable readings are usually distributed mainly because the mean and standard deviation are within the same range for a specific age group. For instance, the systolic blood pressure of a woman aged 18-years-old is normally distributed with the mean as approximately 120 mmHg and 12mmHg as standard deviation. Additionally, in an overall population, BP values follow a smooth, bell-shaped distribution presented in a graph. Height as the other significant variable follows a normal distribution because most data values tend to cluster around the mean (Stovall, Shugart & Yang, 2019). Generally, the normal distribution is remarkably an ideal model of heights for some purposes.
Of the two variables, systolic blood pressure would have a more significant standard deviation since numerous factors trigger pressure to differ, like the health condition and lifestyle. Height remains relatively continuous across the age groups.
Holmes, A., lllowsky, B., & Dean, S. (2017). Introductory business statistics. OpenStax. httgs://ogenstax.org/details/books/introductorY.-business statistics
Stovall, A. E., Shugart, H., & Yang, X. (2019). Tree height explains mortality risk during an intense drought. Nature Communications, 10(1), 1-6. https://doi.org/10.1038/s41467-019-12380-6
Wadhwani, R., Siddiqui, N. I., & Sharma, B. (2018). Assessment of the accuracy of mercury sphygmomanometer and automated oscillometric device of blood pressure measurement in the population of normal individuals. Asian Journal of Medical Sciences, 9(5), 17-24. https://doi.org/10.3126/ajms.v9i5.20469