Setting up directory and importing Dataset

getwd()
## [1] "C:/Users/parvp/Desktop/internship"
titanic.df<-read.csv(paste("Titanic Data.csv", sep=""))
head(titanic.df)
##   Survived Pclass    Sex  Age SibSp Parch    Fare Embarked
## 1        0      3   male 22.0     1     0  7.2500        S
## 2        1      1 female 38.0     1     0 71.2833        C
## 3        1      3 female 26.0     0     0  7.9250        S
## 4        1      1 female 35.0     1     0 53.1000        S
## 5        0      3   male 35.0     0     0  8.0500        S
## 6        0      3   male 29.7     0     0  8.4583        Q

Counting Total Numbers of Passengers

table(titanic.df$Survived)
## 
##   0   1 
## 549 340
addmargins(table(titanic.df$Survived))
## 
##   0   1 Sum 
## 549 340 889

Total number of passengers on board = 889.

Total who survived out of them = 340

prop.table(table(titanic.df$Survived))*100
## 
##        0        1 
## 61.75478 38.24522

38.14522% of passengers survived.

xtabs(~Survived + Pclass, data=titanic.df)
##         Pclass
## Survived   1   2   3
##        0  80  97 372
##        1 134  87 119

134 First class passengers survived the sinking of Titanic.

prop.table(xtabs(~Survived + Pclass, data=titanic.df),2)*100
##         Pclass
## Survived        1        2        3
##        0 37.38318 52.71739 75.76375
##        1 62.61682 47.28261 24.23625

62.61682% of first class passengers survived.

xtabs(~Survived + Pclass + Sex, data=titanic.df)
## , , Sex = female
## 
##         Pclass
## Survived   1   2   3
##        0   3   6  72
##        1  89  70  72
## 
## , , Sex = male
## 
##         Pclass
## Survived   1   2   3
##        0  77  91 300
##        1  45  17  47
ftable((xtabs(~Survived + Pclass + Sex, data=titanic.df)))
##                 Sex female male
## Survived Pclass                
## 0        1               3   77
##          2               6   91
##          3              72  300
## 1        1              89   45
##          2              70   17
##          3              72   47

89 Female passengers survived.

prop.table(xtabs(~Survived + Sex, data=titanic.df),2)*100
##         Sex
## Survived   female     male
##        0 25.96154 81.10919
##        1 74.03846 18.89081

74.03846% of female passengers on board survived.

prop.table(xtabs(~Survived + Sex, data=titanic.df))*100
##         Sex
## Survived    female      male
##        0  9.111361 52.643420
##        1 25.984252 12.260967

25.984% female passengers survived out of 889 passengers including male and female.

chisq.test(xtabs(~Survived + Sex, data=titanic.df))
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  xtabs(~Survived + Sex, data = titanic.df)
## X-squared = 258.43, df = 1, p-value < 2.2e-16

since, p-value is less than 0.05 hence we can safely reject the Null hypothesis