Organization of Data

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Human beings are inquisitive creatures. Since the beginning of time, they have measured, categorized and attempted to understand the world around them. On a daily basis, you can hear these efforts on the evening news and read them in your favorite magazine. Furthermore, to meet this goal, scientist and intellectual explorers arm themselves with the science of statistics. Statistics are applied all in the name of learning something new, proving a point, or perhaps reluctantly admitting there is no connection between two phenomena. The concept of descriptive statistics, the application of descriptive statistics to my own study using a small data set, as well as an example of correlation will be examined.
Descriptive Statistics
For me, the best thing to do when overwhelmed by something is to organize it. In addition to the organization of data, it is desirable to share information about the data in a transparent and concise manner. According to Blessing and Forister (2013), when utilizing descriptive statistics to organize your data the “key concepts are measures of central tendency and measures of variability” (p. 194). These concepts are accomplished by using mean, median, mode, as well as, standard deviation, range and standard error. There value lies in the ability to give information about a set of data, without giving all of the data. There are various situations suited to the different elements of descriptive statistics and it is important to keep in mind the type of data you are using (ordinal, interval, ratio) when selecting the descriptive statistics for your study. In my research study regarding telehealth and 30 day readmission rates, descriptive statistics would be interesting to observe central tendencies for age of th...

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In conclusion, statistics offer a way to organize, measure and understand large sums of data. The way this organization happens depends on the type and size of the data, as well as, the questions trying to be answered. Descriptive statistic’s key concepts are measures of central tendency and measures of variability. In addition, correlation is helpful to find relationships between variables, but not the cause of the relationships. Lastly, it is important to represent your data in an honest and straightforward manner to maintain trust and credibility in the scientific community.

Works Cited

Blessing, J., & Forister, J. (2013). Introduction to research and medical literature for health professionals (Third.). Burlington, MA: Jones & Bartlett Learning.
Grove, S. (2007). Statistics for Health Care Research: A Practical Workbook. Edinburgh: Elsevier Saunders.
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