Assignment 1

Introduction

This is the data analysis from the dataset of insured individuals and their health care claims for populations in Australia. The dataset used for this analysis is titled “dataset-analysis-1.csv”, which contains information on claim types, prices, and other relevant variables.

# library(tidyverse)
# library(readr)
# library(dplyr)
# library(scales)
# dataset_analysis <- read_csv("dataset-analysis-1.csv")

Part 1

Mean and SD of Inpatient Claims

inpatient_summary <- dataset_analysis %>% 
  filter(TYPE_CLAIM == "Inpatient") %>% 
  summarise(
    mean_inpatient = mean(PRICE, na.rm = TRUE),
    sd_inpatient   = sd(PRICE,   na.rm = TRUE)
  )

The mean price for inpatient claims is 4113.16
The standard deviation of inpatient claims is 8075.56.

Mean and SD for Outpatient Claims

outpatient_summary <- dataset_analysis %>% 
  filter(TYPE_CLAIM == "Outpatient") %>% 
  summarise(
    mean_outpatient = mean(PRICE, na.rm = TRUE),
    sd_outpatient   = sd(PRICE,   na.rm = TRUE)
  )

The mean price for inpatient claims is 208.08
The standard deviation of inpatient claims is 380.83.

Percentage (%) of individuals aged <60 and >=60 that claimed

Average Length of Stay (LOS), and SD

los_summary <- dataset_analysis %>% 
  filter(TYPE_CLAIM == "Inpatient") %>% 
  summarise(
    mean_los = mean(LOS, na.rm = TRUE),
    sd_los  = sd(LOS, na.rm = TRUE)
  )

The average LOS is 3.43
The standard deviation of LOS is 11.18

Part 2

a. Total healthcare expenditures (dollars)

b. Are healthcare expenditures positive or 0?

c. Total healthcare expenditures (dollars) if >0

d. Ln (total healthcare expenditures) if >0

expenditures_positive <- expenditures_positive %>%
  mutate(ln_exp = log(total_exp))

ggplot(expenditures_positive, aes(x = ln_exp)) +
  geom_histogram(
    binwidth = 0.5,                      # width of each ln-exp bin
    aes(y = after_stat(count) / sum(after_stat(count))),# convert counts to fraction
    fill = "steelblue",
    color = "black"
  ) +
  scale_y_continuous(labels = number_format(accuracy = 0.1)) +
  labs(
    title = "Fraction of Individuals by ln(Total Healthcare Expenditures) (>0)",
    x = "ln(Total Expenditures)",
    y = "Percentage of Individuals"
  ) +
  theme_minimal()

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