MATH225N Week 5 Discussion The Normal Distribution

Professor and Class, Statistics is essential and vital to the healthcare team, as the knowledge acquired is crucial to the practice of medical science (Kim et al., 2020). One element of statistical data is normality , and normality possesses a characteristic property of a random variable or quantity, described casually as a variable whose values depend on the outcome of a random occurrence. It presents a distinctive distribution that resembles a symmetrical bell curve. Half of the data will fall to the left of the mean; half will fall to the right. Two examples of variables that would have a normal distribution include the body weight and blood pressure among the adults in a population. In identifying the variability in the bodyweight among adults in a population, one must first measure each subject weight and then summarize the findings as shown in the graph. The graph Illustrates the different body weights on the horizontal axis ( the X-axis ) and the frequency (% of subjects ) on the vertical axis ( the Y-axis ) as displayed on the left side of the graph. Several characteristics to be aware of are bell -shaped appearance of the curve with a single peak in the center and its symmetric shape . If the distribution is symmetrical with a single peak in the center, the mean value, the mode, and the median will all appear to be the same. The height additionally follows a normal distribution as well, in the sense that most of the data values tend to cluster around the mean and remain constant across age groups. Many variables have similar characteristics known as normal distributions (Holmes et al., 2017). The horizontal or X-axis displays the scale characteristics of the weight analyzed in the graph; the height of the middle curve shows the probability of observing each value. As the curve shows its highest point in the middle, it suggests that the values have a higher occurrence and are more likely to occur , and the curve tails off above and below the middle curve suggest values at either extreme that are less likely to occur. A healthy blood pressure (BP) is another variable. Systolic blood pressure has a distributive property, given that the average standard deviation is within the same range for a particular age group. The distribution of blood pressure status is statistically different across gender, race or ethnicity, and age groups (Grandner et al., 2018). For example, adults aged 19–

40 are likely to be normotensive than those in the older age groups. The mean systolic blood pressure of an 18-year-old woman or older can have a normal distribution of the mean of approximately 120 mmHg, and the change in measured blood pressure will therefore have a mean of 10 mm Hg and a standard deviation of 13 mm Hg according to Oxford Academic Journal, 2008). Estimated Blood Pressure Ranges (mmHg) Age Systolic-Range Diastolic-Range Adolescent (14 – 18 years) 90-120 50-80 Adult (19 – 40 years) 95-135 60-80 Conclusively, there are chances that the systolic blood pressure is likely to have a higher standard deviation due to underlining factors that may cause pressure to vary, factors like an individual’s medical health condition such as pregnancy, disease process, individual lifestyle, etc. References Grandner, M., Mullington, J. M., Hashmi, S. D., Redeker, N. S., Watson, N. F., & Morgenthaler, T. I. (2018). Sleep duration and hypertension: analysis of> 700,000 adults by age and sex. Journal of Clinical Sleep Medicine , 14 (6), 1031-1039. https://doi.org/10.5664/jcsm.7176 Holmes, A., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. OpenStax. p.6 Retrieved from: https://openstax.org/details/books/introductory-business- statistics (Links to an external site.) (Links to an external site.) Kim, M., Mallory, C., & Valerio, T. (2020). Statistics for evidence-based practice in nursing . Jones & Bartlett Publishers. Prof and class, "The normal probability density function, a continuous distribution, is the most important of all the distributions" (Holmes, A., Illowsky, B., & Dean, S.,2017). Two examples in the medical field that follow a normal distribution are blood pressure and height. For blood pressure and height, a normal distribution would allow researchers and people to see what is average and where people lie in those categories. It's important to know where you fall on the spectrum in order to catch potential health problems. For example, if the average

mortality. The normal resting heart rate for adults ranges from 60-90 beats per minutes (Avram, et al., 2019). The normal systolic blood pressure is less than 120 mmHg. Therefore, systolic blood pressure is likely to have a larger standard deviation because an individual with normal blood pressure may have a BP reading of 75 mmHg while an individual with an uncontrolled BP may have a BP of more than 180. Therefore, the range is significantly high in BP than in heart rate measurements. References Avram, R., Tison, G. H., Aschbacher, K., Kuhar, P., Vittinghoff, E., Butzner, M., ... & Olgin, J. (2019). Real-world heart rate norms in the Health eHeart study. NPJ Digital Medicine , 2 (1), 1-10. https://dx.doi.org/10.1038%2Fs41746-019-0134-9 (Links to an external site.) Diaz, A. A. (2018). Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants. International Journal of Epidemiology , 47 (3), 872–883i. https://doi.org/10.1093/ije/dyy016 (Links to an external site.) McLeod, S. (2020). Introduction to the normal distribution (bell curve). https://www.simplypsychology.org/normal-distribution.html