Reading the dataset.
setwd("~/R")
titanic.df<-read.csv(paste("Titanic Data.csv",sep = ""))
Count the total number of passengers on board the Titanic.
nrow(titanic.df)
## [1] 889
Count the number of passengers who survived the sinking of the Titanic.
mytable <- with(titanic.df, table(Survived))
mytable
## Survived
## 0 1
## 549 340
Measure the percentage of passengers who survived the sinking of the Titanic.
mytable <- with(titanic.df, table(Survived))
prop.table(mytable)*100
## Survived
## 0 1
## 61.75478 38.24522
Count the number of first-class passengers who survived the sinking of the Titanic.
mytable <- xtabs(~ Pclass+Survived, data=titanic.df)
mytable
## Survived
## Pclass 0 1
## 1 80 134
## 2 97 87
## 3 372 119
Measure the percentage of first-class passengers who survived the sinking of the Titanic.
mytable <- xtabs(~ Pclass+Survived, data=titanic.df)
prop.table(mytable)*100
## Survived
## Pclass 0 1
## 1 8.998875 15.073116
## 2 10.911136 9.786277
## 3 41.844769 13.385827
Count the number of females from First-Class who survived the sinking of the Titanic.
mytable <- xtabs(~ Pclass+Survived+Sex, data=titanic.df)
mytable
## , , Sex = female
##
## Survived
## Pclass 0 1
## 1 3 89
## 2 6 70
## 3 72 72
##
## , , Sex = male
##
## Survived
## Pclass 0 1
## 1 77 45
## 2 91 17
## 3 300 47
Count the percentage of females from First-Class who survived the sinking of the Titanic.
mytable <- xtabs(~ Pclass+Survived+Sex, data=titanic.df)
prop.table(mytable)*100
## , , Sex = female
##
## Survived
## Pclass 0 1
## 1 0.3374578 10.0112486
## 2 0.6749156 7.8740157
## 3 8.0989876 8.0989876
##
## , , Sex = male
##
## Survived
## Pclass 0 1
## 1 8.6614173 5.0618673
## 2 10.2362205 1.9122610
## 3 33.7457818 5.2868391
Measure the percentage of females on board the Titanic who survived.
mytable <- xtabs(~ Survived+Sex, data=titanic.df)
prop.table(mytable)*100
## Sex
## Survived female male
## 0 9.111361 52.643420
## 1 25.984252 12.260967
Pearson’s Chi-squared test to test the following hypothesis:
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.
mytable <- xtabs(~ Survived+Sex, data=titanic.df)
addmargins(mytable)
## Sex
## Survived female male Sum
## 0 81 468 549
## 1 231 109 340
## Sum 312 577 889
chisq.test(mytable)
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: mytable
## X-squared = 258.43, df = 1, p-value < 2.2e-16
This output suggests a relationship between ‘Sex’ and ‘Survived’.