Assignment of analysing data of Sinking of the RMS Titanic.
titanic <- read.csv(paste("Titanic Data.csv", sep=""))
View(titanic)
head(titanic)
## 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
summary(titanic)
## Survived Pclass Sex Age
## Min. :0.0000 Min. :1.000 female:312 Min. : 0.40
## 1st Qu.:0.0000 1st Qu.:2.000 male :577 1st Qu.:22.00
## Median :0.0000 Median :3.000 Median :29.70
## Mean :0.3825 Mean :2.312 Mean :29.65
## 3rd Qu.:1.0000 3rd Qu.:3.000 3rd Qu.:35.00
## Max. :1.0000 Max. :3.000 Max. :80.00
## SibSp Parch Fare Embarked
## Min. :0.0000 Min. :0.0000 Min. : 0.000 C:168
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 7.896 Q: 77
## Median :0.0000 Median :0.0000 Median : 14.454 S:644
## Mean :0.5242 Mean :0.3825 Mean : 32.097
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.: 31.000
## Max. :8.0000 Max. :6.0000 Max. :512.329
dim(titanic)
## [1] 889 8
Here, we see that there are 889 total entries which includes details of all the onboard passangers. Hence, total number of passangers onboard = 889.
ttable <- with(titanic, table(titanic$Survived))
ttable
##
## 0 1
## 549 340
Here, 1= survived and 0= not servived. Hence there were 340 passangers who survived sinking of Titanic.
cent_ser <-prop.table(ttable)*100
cent_ser
##
## 0 1
## 61.75478 38.24522
Here, there were 38.24% passangers survived sinking of Titanic.
ttable2 <- xtabs(~ titanic$Survived+titanic$Pclass, data=titanic)
ttable2
## titanic$Pclass
## titanic$Survived 1 2 3
## 0 80 97 372
## 1 134 87 119
ttable2[2]
## [1] 134
Number of First class passangers survived are 134.
first_cent_ser <-prop.table(ttable2)*100
first_cent_ser
## titanic$Pclass
## titanic$Survived 1 2 3
## 0 8.998875 10.911136 41.844769
## 1 15.073116 9.786277 13.385827
Out of total passangers, 15.07% first class passangers were survived. This is highest survival rate among all the classes.
ttable3 <- xtabs(~ titanic$Survived+titanic$Pclass+titanic$Sex, data=titanic)
ftable(ttable3)
## titanic$Sex female male
## titanic$Survived titanic$Pclass
## 0 1 3 77
## 2 6 91
## 3 72 300
## 1 1 89 45
## 2 70 17
## 3 72 47
89 were female first class surivers.
ttable4 <- xtabs(~ titanic$Survived + titanic$Sex,data=titanic)
ttable4
## titanic$Sex
## titanic$Survived female male
## 0 81 468
## 1 231 109
Totla 231 females survived.
prop.table(ttable4,2)*100
## titanic$Sex
## titanic$Survived female male
## 0 25.96154 81.10919
## 1 74.03846 18.89081
74.03% of females who boarded Titanic survived.
Hypothesis: The proportion of females onboard who survived the sinking of the Titanic was higher than the proportion of males onboard who survived the sinking of the Titanic.
chisq.test(ttable4)
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: ttable4
## X-squared = 258.43, df = 1, p-value < 2.2e-16
This test suggests that wather passanger will survive or not it will depend upon the gender of the survivor. P value is less than the acceptable P(<0.05), hence, this relationship is significant.