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Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clinic in a month’s time. The second set contains data on the number of minutes that each patient spent in the waiting room of a doctor’s office. You can make assumptions about other information or variables that are included in each data set.

For each data set, propose your idea of how best to represent the key information. 
To organize your data would you choose to use a frequency table, a cumulative frequency table, or a relative frequency table? Why?

For my first data set, I use a relative frequency table. I chose this because we can take the age range and use that data in our class. So in August, we had a range of people whose age was as follows: 22, 40, 60, 55, 42, 62, 28, 30, 48, 25. I chose this table because this information is vital at the administrative level as it shows the clinics’ demography to the percentage. This would allow the clinic to know what type of patients they see most often and would allow the administrator to order supplies based on the concentration of age group(Manikandan, S. 2011). For instance in this case it wouldn’t make sense for the clinic to buy children-specific equipment as their demographic are adult patients.

For the second data set, I would choose a frequency table. I chose this table because it is simple data. It would give the office manager a start point to see how long the patients are waiting. As demonstrated by this data, the majority of patients are waiting over 30 minutes to be seen. This could lead to further inquiry by the manager as to why this is happening. It would be simple to obtain this data. A patient would be given a stamped ticket when they register and it would get stamped again when they are seen. 

What type of graph would you use to display the organized data from each frequency distribution? What would be shown on each of the axes for each graph?

For both my data sets I would use histograms as a way to present data visual way to present probabilities of different categories by the simple visual of comparing relative areas in each category(Holmes et al., 2017). On the 
x-axis, I could place the time waiting, and on the y-axis the associated people who waited that long to be seen.

References

Holmes, A., Illowsky, B., & Dean, S. D. (2017). Introductory Business Statistics. OpenStax. 

https://openstax.org/books/introductory-business-statistics/pages/2-1-display-dataLinks to an external site.

Manikandan S. (2011). Frequency distribution. 
Journal of pharmacology & pharmacotherapeutics, 
2(1), 54–56. https://doi.org/10.4103/0976-500X.77120