Hospital Patient Blood Pressure Analysis: Boxplots and Histogram

 

    For this assignment, I analyzed hospital patient data to examine how blood pressure relates to doctors’ assessments and final treatment decisions. The dataset includes 10 patients and contains information on visit frequency, blood pressure, doctor evaluations, and final care decisions. Using R, I created boxplots and a histogram to visualize patterns in the data.

Methods

I entered the dataset into R and converted the doctor assessments into numeric values. I then created:

  • A basic boxplot of blood pressure

  • Side-by-side boxplots comparing blood pressure with doctor ratings

  • A histogram showing the overall distribution of blood pressure

I also calculated summary statistics to support my interpretation.

Results

Boxplots


The boxplots compare blood pressure with:

  • First doctor rating (good vs bad)

  • Second doctor assessment (low vs high)

  • Final decision (low vs high)

Histogram



The histogram shows the overall distribution of blood pressure values.

Discussion

Blood pressure values are widely spread, ranging from 32 to 205, with a median of 95 and a mean of 102.6. The histogram and boxplot show a right-skewed distribution caused by the very high value of 205, which increases the average.

When grouped by the second doctor’s assessment, patients rated as “high” tend to have higher blood pressure. The high group has a median of 106.5 and includes the highest values, while the low group has a median of 95 and a smaller range.

The final decision shows the clearest difference. Patients with a “low” final decision have much lower blood pressure overall (median 68.5, maximum 103), while those with a “high” final decision have much higher blood pressure (median 122, maximum 205). This suggests that blood pressure strongly influences the final treatment decision.

The first doctor’s rating shows more overlap between groups. Some patients rated “good” still had high blood pressure, including the highest value in the dataset. One patient’s first rating was missing and was omitted from that analysis.

Overall, higher blood pressure is most strongly associated with the second doctor’s assessment and the final decision.

Conclusion

This analysis shows that blood pressure plays an important role in medical decision-making, especially in the final evaluation. Using boxplots and histograms made it easier to identify outliers, trends, and group differences in the data.


 

 

 

 

 

 

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