Titanic Case Study:Assignment 1

This is a case study on the sinking of the Titanic ship.

Reading and Viewing the Titanic Database

setwd("D:/desktop/Data Analytics internship-sameer mathur/work/datasets")
titanic.df<-read.csv(paste("Titanic Data.csv", sep=""))
View(titanic.df)

3a: Number of passengers on board

length(titanic.df$Survived)
## [1] 889

There were 889 passengers on board the Titanic.

3b: the number of passengers who survived the sinking of the Titanic

with(titanic.df, table(Survived))
## Survived
##   0   1 
## 549 340

340 passengers survived the sinking of the Titanic.

3c: the percentage of passengers who survived the sinking of the Titanic

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

Only 38.24522% of the passengers survived and the rest 61.75478% died.

3d: the number of first-class passengers who survived the sinking of the Titanic

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

134 first class passengers survived.

3e: the percentage of first-class passengers who survived the sinking of the Titanic

prop.table(mytable)*100
##         Pclass
## Survived         1         2         3
##        0  8.998875 10.911136 41.844769
##        1 15.073116  9.786277 13.385827

Of the total no. of passengers who were on board, the percentage of first class passengers who survived is 15.073116%.

3f: the number of females from First-Class who survived the sinking of the Titanic

mytable <- xtabs(~ Survived+Pclass+Sex, data=titanic.df)
mytable
## , , 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

The number of females from First-Class who survived the sinking of the Titanic is 89.

3g: the percentage of survivors who were female

mytable <- xtabs(~ Survived+Sex, data=titanic.df)
mytable
##         Sex
## Survived female male
##        0     81  468
##        1    231  109
prop.table(mytable,1)*100
##         Sex
## Survived   female     male
##        0 14.75410 85.24590
##        1 67.94118 32.05882

The total numberr of female survivors is 231 and it is 67.94118% of the total survivors.

3h: the percentage of females on board the Titanic who survived

prop.table(mytable,2)*100
##         Sex
## Survived   female     male
##        0 25.96154 81.10919
##        1 74.03846 18.89081

The percentage of females on board the Titanic who survived is 74.03846%.

3i: Chi-squared test

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(~ Sex+Survived, data=titanic.df)
mytable
##         Survived
## Sex        0   1
##   female  81 231
##   male   468 109
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

Since the p-value is vey small(<0.01), we reject the Null hypothesis.