Titanic

R Markdown

The dataset is checked and viewed.

tsa.df<-read.csv(paste("Titanic Data.csv"))
View(tsa.df)

Including Plots

The margins are added. There are total 890 passengers. 340 survived.

## Survived
##   0   1 Sum 
## 549 340 889

38.2% of passengers survived.

prop.table(mytable)

## Survived
##         0         1 
## 0.6175478 0.3824522

mytable2<-xtabs(~Pclass+Survived, data=tsa.df)
mytable2

##       Survived
## Pclass   0   1
##      1  80 134
##      2  97  87
##      3 372 119

62.6% of first-class passengers survived

prop.table(mytable2,1)

##       Survived
## Pclass         0         1
##      1 0.3738318 0.6261682
##      2 0.5271739 0.4728261
##      3 0.7576375 0.2423625

89 females from first class survived

mytable3<-xtabs(~Sex+Survived+Pclass, data=tsa.df)
mytable3

## , , Pclass = 1
## 
##         Survived
## Sex        0   1
##   female   3  89
##   male    77  45
## 
## , , Pclass = 2
## 
##         Survived
## Sex        0   1
##   female   6  70
##   male    91  17
## 
## , , Pclass = 3
## 
##         Survived
## Sex        0   1
##   female  72  72
##   male   300  47

74% females survived

mytable4<-xtabs(~Sex+Survived, data=tsa.df)
prop.table(mytable4,1)

##         Survived
## Sex              0         1
##   female 0.2596154 0.7403846
##   male   0.8110919 0.1889081

Since p-value<0.01, null hypothesis can be rejected.

chisq.test(mytable4)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  mytable4
## X-squared = 258.43, df = 1, p-value < 2.2e-16

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.