The indicators of the normal distribution of variables in medicine can be used for different purposes, for example, in calculating disease dynamics, growth data, and in other cases. With this distribution, most of the values are grouped around some average indicator, and on both sides of it, the frequency of observations decreases evenly. The ideal curve of the graph showing the movement of variable parameters is the shape of the bell where there are a rise and a sharp decline.
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This type of data dynamics does not always occur and is considered standard. Normal distribution means the value that is closest to the average. According to Jin et al. (2016), “values of normal variables are presented as the mean ± standard deviation (SD) and those of nonnormal variables as the median and interquartile range” (p. 69). This formulation allows all calculations to be performed based on the indicators of the average results.
As the examples of variables that are likely to follow a normal distribution, it is possible to use the data of people undergoing treatment in the inpatient department. For instance, the data on blood pressure in hypertensive patients can be compared with the parameters received during weight gain in patients with a lack of body weight. In this case, the first parameter will have a larger standard deviation because, under the influence of the disease, the pressure values will often change.
If appropriate treatment is applied to patients with a lack of body weight, the process of recovery will be stable, and this indicator will deviate less from the norm than the previous one. Thus, these examples may illustrate the potential difference in values and deviation.
Jin, C., Peng, X., Xie, T., Lu, X., Liu, F., Wu, H.,… Wu, N. (2016). Detection of the long noncoding RNAs nuclear-enriched autosomal transcript 1 (NEAT1) and metastasis associated lung adenocarcinoma transcript 1 in the peripheral blood of HIV-1-infected patients. HIV Medicine, 17(1), 68-72. Web.