Cancer Survival

cancer = read.csv("cancer-survival.csv", header = TRUE)
str(cancer)

## 'data.frame':    64 obs. of  2 variables:
##  $ Survival: int  124 42 25 45 412 51 1112 46 103 876 ...
##  $ Organ   : Factor w/ 5 levels "Breast","Bronchus",..: 5 5 5 5 5 5 5 5 5 5 ...

summary(cancer)

##     Survival           Organ   
##  Min.   :  20.0   Breast  :11  
##  1st Qu.: 102.5   Bronchus:17  
##  Median : 265.5   Colon   :17  
##  Mean   : 558.6   Ovary   : 6  
##  3rd Qu.: 721.0   Stomach :13  
##  Max.   :3808.0

levels(cancer$Organ)

## [1] "Breast"   "Bronchus" "Colon"    "Ovary"    "Stomach"

boxplot(cancer$Survival~ cancer$Organ, xlab="Organs with Cancer", ylab="Survival Times")
title("Survival Times from Cancer Types with Ascorbate Treatment")
means1 <- by(cancer$Survival, cancer$Organ, mean)
points(1:5, means1, pch = 23, cex = 1, bg = "blue")
text(1:5 - 0.1, means1,labels = format(means1, format = "f", digits = 0),pos = 3, cex = 0.9, col = "blue")

round(means1, digits = 2)

## cancer$Organ: Breast
## [1] 1395.91
## -------------------------------------------------------- 
## cancer$Organ: Bronchus
## [1] 211.59
## -------------------------------------------------------- 
## cancer$Organ: Colon
## [1] 457.41
## -------------------------------------------------------- 
## cancer$Organ: Ovary
## [1] 884.33
## -------------------------------------------------------- 
## cancer$Organ: Stomach
## [1] 286

model_1 <- aov(cancer$Survival~ cancer$Organ)
anova(model_1)

## Analysis of Variance Table
## 
## Response: cancer$Survival
##              Df   Sum Sq Mean Sq F value    Pr(>F)    
## cancer$Organ  4 11535761 2883940  6.4334 0.0002295 ***
## Residuals    59 26448144  448274                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1