Read the titanic data set into R . Create a dataframe called “titanic”.
setwd("C:/Users/Prabha Shankar/Desktop/Winter Internship/R file")
titanic <- read.csv("Titanic Data.csv")
View(titanic)
use R to count the total number of passengers on bord the Titanic.
dim(titanic)
## [1] 889 8
Total number of passenger on bord the titanic is 889.
Use R to count the nuumber of passengers who survived the sinking of Titanic.
var1 <- table(titanic$Survived)
var1[2]
## 1
## 340
Total no of passengers who survived the sinking of Titanic is 340.
Use R to measure the percentage of passengers who survived the sinking of the Titanic.
var2 <- prop.table(var1)*100
var2[2]
## 1
## 38.24522
percentage of passengers who survived the sinking of the titanic is 38.24522.
Use R to count the number of first class passengers who survived the sinking of the titanic
var3 <-xtabs(~Survived+Pclass , data=titanic)
var3[1][1]
## [1] 80
Number of first class passengers who survived the sinking of the titancic is 80
Use R to measure the percentage of first class passengers who survived the sinking of the Titanic
var4 <- prop.table(var3)*100
var4[1][1]
## [1] 8.998875
Percentage of first class passengers who survived the sinking of the titanic is 8.998875
Use R to count the number of females from Firsr class who survived the sinking of the titanic
var5 <- xtabs(~Survived+Pclass+Sex , data=titanic)
var5[2][1]
## [1] 89
Number of females from first class who suvived the sinking of the titanic is 89
Use R to calculate the percentage of survivors who were female
var6 <- xtabs(~Survived+Sex , data = titanic)
var7<-prop.table(var6,1)*100
var7
## Sex
## Survived female male
## 0 14.75410 85.24590
## 1 67.94118 32.05882
Percentage of the survivors who were female is 67.94118.
USe R to measure the percentage of females on board the titanic who survived.
var8 <- prop.table(var6,2)*100
var8
## Sex
## Survived female male
## 0 25.96154 81.10919
## 1 74.03846 18.89081
Percentage of females on board the titanic who survived is 74.03846
Run a Pearson’s Chi-Squared test to test the hypothesis .
chisq.test(var8)
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: var8
## X-squared = 58.934, df = 1, p-value = 1.631e-14