Loading Data

library(readr)
data_M5 <- read_csv("C:/Users/gmutya048/Downloads/data (3).csv")
## 
## -- Column specification --------------------------------------------------------
## cols(
##   `Patient ID` = col_double(),
##   Gender = col_character(),
##   Race = col_character(),
##   Treatment = col_character(),
##   Improved = col_character()
## )

Analysis

nd<-chisq.test(data_M5$Improved,data_M5$Treatment)
nd
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  data_M5$Improved and data_M5$Treatment
## X-squared = 15.994, df = 1, p-value = 6.356e-05
nd$observed
##                 data_M5$Treatment
## data_M5$Improved Placebo Treated
##                N      38      17
##                Y       9      28
nd$expected
##                 data_M5$Treatment
## data_M5$Improved  Placebo  Treated
##                N 28.09783 26.90217
##                Y 18.90217 18.09783

There is a statistical relationship between Treatment and Improved (χ2 =15.994 and p-value=6.356e-05).

Tables and Figures

library(vcd)
## Loading required package: grid
mosaic(~Treatment +Improved, data = data_M5, shade=TRUE, legend=TRUE , main = "Improved", labeling = labeling_values)