Data

setwd("C:/Users/kvr104/Downloads/Data")

tab1<-read.delim("PUDF_base1_1q2020_tab.txt")

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.6.1

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

tab_clean <- tab1[complete.cases(tab1$LENGTH_OF_STAY, tab1$TOTAL_CHARGES_ANCIL), ]

``` r
mode(tab_clean$LENGTH_OF_STAY)

## [1] "numeric"

summary(tab_clean$LENGTH_OF_STAY)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##    1.000    2.000    3.000    5.461    6.000 5433.000

summary(tab_clean$TOTAL_NON_COV_CHARGES_ANCIL)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##        0        0        0     2675        0 48210100

TCA<- tab_clean[tab_clean$TOTAL_CHARGES_ANCIL !=0, ]

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.6.1

tab_clean %>%
  filter(TOTAL_CHARGES_ANCIL != 0) %>%
  ggplot(aes(x = TOTAL_CHARGES_ANCIL, y = LENGTH_OF_STAY)) +
  geom_point()

library(dplyr)

tab_clean %>% 
  filter(TOTAL_CHARGES_ANCIL != 0) %>% 
  summarize(correlation = cor(TOTAL_CHARGES_ANCIL, LENGTH_OF_STAY, use = "complete.obs"))

##   correlation
## 1   0.5147687