Frequency and descriptive statistics
Imagine that you have collected data from 100 patients. You have carefully compiled vitals, pain scores, and medications for each of the patients. However,
what does all of this data mean? Is your work now done?
How do we make data meaningful? Why must we move beyond the raw data to ensure that data is purposeful?
Descriiptive analysis is the analysis of the data to develop meaning. Descriiptive analysis provides meaning through showing, describing, and summarizing
the data compiled to “reveal characteristics of the sample and to describe study variables” (Gray & Grove, 2020). This allows the researcher to present data in
a more meaningful and simplified way.
For this Assignment, summarize your interpretation of the descriiptive statistics provided to you in the Week 4 Descriiptive Statistics SPSS Output document.
You will evaluate each variable in your analysis.
The third variable is pain score, with an average score of 6 and a standard deviation of 1.75 This indicates that there was some variability in pain scores among the patient population, with none experiencing extreme levels (above 8 or below 4) on average.
The fourth variable is pulse rate, which has an average rate of 89 beats per minute and a standard deviation of 18 beats per minute. This suggests that heart rates were generally consistent across all patients, with no outliers beyond 107 or 71 beats per minute on either end.
Finally, the fifth variable is medications used by patients to manage their conditions during this study period; this includes nonsteroidal anti-inflammatory drugs (NSAID), opiate analgesics (OA), antidepressants (ADT), anticonvulsants/antiepileptics (A/A) drugs ,and sedatives/hypnotics (SH). The data showed that NSAIDs were used most often by 76% of participants followed by OAs at 65%, ADTs at 58%, A/As at 42%, and SHs at 14%. This suggests that NSAIDs are the most commonly prescribed medications for managing pain as well as other symptoms in this population studied here.