Homework 5

#Homework 5
data<-read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/refs/heads/main/RadDat_IMSE.csv")

#1
medicare<-data[data$PatientAge>=65,]
q1<-quantile(medicare$Ordered.to.Complete...Mins)[2]
q3<-quantile(medicare$Ordered.to.Complete...Mins)[4]
medicare.iqr<-medicare[medicare$Ordered.to.Complete...Mins>=q1 & medicare$Ordered.to.Complete...Mins<=q3,]
hist(medicare.iqr$Ordered.to.Complete...Mins,main="medicare completion times", xlab = "mins to complete",ylab = "frequency")

#Most completion times are at lower values and smaller numbers require a longer completion time
#2 
median(data[data$Radiology.Technician==62,"Ordered.to.Complete...Mins"])

## [1] 80

median(data[data$Radiology.Technician==63,"Ordered.to.Complete...Mins"])

## [1] 18

median(data[data$Radiology.Technician==64,"Ordered.to.Complete...Mins"])

## [1] 82

median(data[data$Radiology.Technician==65,"Ordered.to.Complete...Mins"])

## [1] 27

#Technician 63 had the lowest completion time

#3
stat<-data[data$Priority=="STAT",]
routine<-data[data$Priority=="Routine",]
boxplot(stat$PatientAge,routine$PatientAge,names=c("STAT","Routine"),main="Patient Age Comparison",xlab="Order",ylab="Patient Age")

#The boxplot shows that patients with rountine orders tend to be older that patients with stat orders
#4
floor3W<-data[data$Loc.At.Exam.Complete=="3W",]
mean(floor3W$Ordered.to.Complete...Mins)

## [1] 1463.051

sd(floor3W$Ordered.to.Complete...Mins)

## [1] 3894.639

floor4W<-data[data$Loc.At.Exam.Complete=="4W",]
mean(floor4W$Ordered.to.Complete...Mins)

## [1] 1675.451

sd(floor4W$Ordered.to.Complete...Mins)

## [1] 4387.644

#4W mean time is higher, indicating that x-ray orders usually take longer to complete