Load github file:

Read in x-ray data and filter

dataset <- "https://raw.githubusercontent.com/tmatis12/datafiles/refs/heads/main/RadDat_IMSE.csv"


xray_orders<- read.csv(dataset)

names(xray_orders)
##  [1] "Unique.Identifier"           "PatientAge"                 
##  [3] "Radiology.Technician"        "CatalogCode"                
##  [5] "Ordering.Physician"          "PatientTypeMnemonic"        
##  [7] "Priority"                    "OrderDateTime"              
##  [9] "ExamCompleteDateTime"        "FinalDateTime"              
## [11] "Ordered.to.Complete...Mins"  "Ordered.to.Complete...Hours"
## [13] "Loc.At.Exam.Complete"        "Exam.Completed.Bucket"      
## [15] "Section"                     "Exam.Room"
#filter time complete order

xray_orders <- xray_orders[xray_orders$Ordered.to.Complete...Mins >= 0, ]

xray_orders <- xray_orders[xray_orders$Ordered.to.Complete...Hours >= 0, ]

Question 1.

Plost Histogram

Patients that are age 65 or older quality for Medicare.  Generate a histogram on the time required to fulfill X-ray orders for Medicare patients, restricting the allowable range of times to be between the first and third quartile of observations, i.e. the IQR.

#select age columns
xray_orders <- xray_orders[xray_orders$PatientAge >= 65, ]

q1 <- quantile(xray_orders$Ordered.to.Complete...Mins, 0.25, names = TRUE)

q3 <- quantile(xray_orders$Ordered.to.Complete...Mins, 0.75, names = TRUE)

xray_orders <- xray_orders[xray_orders$Ordered.to.Complete...Mins >= q1 &
                xray_orders$Ordered.to.Complete...Mins <= q3, ]

#Histogram!!!!
hist(xray_orders$Ordered.to.Complete...Mins, main = "Histogram of X-Ray Order Time",
     xlab = "Time to complete",
     ylab = "x-ray orders",
     col = "navy",
     border = "magenta")

Histogram Shape:

I would say that the histogram is skewed far right hinting at the completion times being relatively quick.

Question 2:

Median time for technicians

Create range for technician

rtech_range <- xray_orders[xray_orders$Radiology.Technician %in% 62:65, ]

Calculate median

Interpretation:

My chunk to calculate the median only put out 3 technicians, so this is as far as I got.

Question 3:

SidebySide Boxplot

Question 4:

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