Module # 4 Programming structure assignment

Github link: https://github.com/rayhankhan-svg/r-programming-assignments

R Code:

# Create the data vectors

Frequency <- c(0.6, 0.3, 0.4, 0.4, 0.2, 0.6, 0.3, 0.4, 0.9, 0.2)


BloodPressure <- c(103, 87, 32, 42, 59, 109, 78, 205, 135, 176)


First <- c("bad", "bad", "bad", "bad", "good", "good", "good", "good", NA, "bad")


Second <- c("low", "low", "high", "high", "low", "low", "high", "high", "high", "high")


FinalDecision <- c("low", "high", "low", "high", "low", "high", "low", "high", "high", "high")


# Create data frame

hospital_data <- data.frame(Frequency, BloodPressure, First, Second, FinalDecision)


hospital_data



# Create boxplot of Blood Pressure

boxplot(BloodPressure,

        main="Boxplot of Patient Blood Pressure",

        ylab="Blood Pressure",

        col="lightblue")



# Create histogram of Blood Pressure

hist(BloodPressure,

     main="Histogram of Patient Blood Pressure",

     xlab="Blood Pressure",

     col="lightgreen")


Output:
> # Create the data vectors
> Frequency <- c(0.6, 0.3, 0.4, 0.4, 0.2, 0.6, 0.3, 0.4, 0.9, 0.2)
> 
> BloodPressure <- c(103, 87, 32, 42, 59, 109, 78, 205, 135, 176)
> 
> First <- c("bad", "bad", "bad", "bad", "good", "good", "good", "good", NA, "bad")
> 
> Second <- c("low", "low", "high", "high", "low", "low", "high", "high", "high", "high")
> 
> FinalDecision <- c("low", "high", "low", "high", "low", "high", "low", "high", "high", "high")
> 
> # Create data frame
> hospital_data <- data.frame(Frequency, BloodPressure, First, Second, FinalDecision)
> 
> hospital_data
   Frequency BloodPressure First Second FinalDecision
1        0.6           103   bad    low           low
2        0.3            87   bad    low          high
3        0.4            32   bad   high           low
4        0.4            42   bad   high          high
5        0.2            59  good    low           low
6        0.6           109  good    low          high
7        0.3            78  good   high           low
8        0.4           205  good   high          high
9        0.9           135  <NA>   high          high
10       0.2           176   bad   high          high
> 
> 
> # Create boxplot of Blood Pressure
> boxplot(BloodPressure,
+         main="Boxplot of Patient Blood Pressure",
+         ylab="Blood Pressure",
+         col="lightblue")
> 
> 
> # Create histogram of Blood Pressure
> hist(BloodPressure,
+      main="Histogram of Patient Blood Pressure",
+      xlab="Blood Pressure",
+      col="lightgreen")
> 
















Explanation: 

I developed a data frame using hospital patient information for this assignment, such as visit frequency, blood pressure readings, and physician evaluations. After that, I created a boxplot and a histogram to show how the blood pressure readings of the patients were distributed. The majority of patients had blood pressure readings in the moderate range, according to the boxplot and histogram, but some had higher readings that would point to possible health issues. The histogram displayed the frequency distribution of blood pressure readings, while the boxplot assisted in identifying the dispersion and any outliers. Higher blood pressure readings were more frequently linked to high-risk conclusions, suggesting that the doctors' assessments and ultimate choices were impacted by the data. This exercise showed how R's graphical capabilities, such as boxplots and histograms, may be used to effectively depict and interpret medical data.






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