Reading the TitanicData.csv file

titanic.df <- read.csv(paste("TitanicData.csv", sep=""))
attach(titanic.df)

Decribing the file

library(psych)
describe(titanic.df)
##           vars   n  mean    sd median trimmed   mad min    max  range
## Survived     1 889  0.38  0.49   0.00    0.35  0.00 0.0   1.00   1.00
## Pclass       2 889  2.31  0.83   3.00    2.39  0.00 1.0   3.00   2.00
## Sex*         3 889  1.65  0.48   2.00    1.69  0.00 1.0   2.00   1.00
## Age          4 889 29.65 12.97  29.70   29.22  9.34 0.4  80.00  79.60
## SibSp        5 889  0.52  1.10   0.00    0.27  0.00 0.0   8.00   8.00
## Parch        6 889  0.38  0.81   0.00    0.19  0.00 0.0   6.00   6.00
## Fare         7 889 32.10 49.70  14.45   21.28 10.24 0.0 512.33 512.33
## Embarked*    8 889  2.54  0.79   3.00    2.67  0.00 1.0   3.00   2.00
##            skew kurtosis   se
## Survived   0.48    -1.77 0.02
## Pclass    -0.63    -1.27 0.03
## Sex*      -0.62    -1.61 0.02
## Age        0.43     0.96 0.43
## SibSp      3.68    17.69 0.04
## Parch      2.74     9.66 0.03
## Fare       4.79    33.23 1.67
## Embarked* -1.26    -0.23 0.03

Table showing the average age of the survivors and the average age of the people who died.

aggregate(titanic.df$Age ~ titanic.df$Survived, data = titanic.df, FUN = mean)
##   titanic.df$Survived titanic.df$Age
## 1                   0       30.41530
## 2                   1       28.42382

T-test to test the following hypothesis:

H:The Titanic survivors were younger than the passengers who died.

t.test(Age ~ Survived, data=titanic.df)
## 
##  Welch Two Sample t-test
## 
## data:  Age by Survived
## t = 2.1816, df = 667.56, p-value = 0.02949
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.1990628 3.7838912
## sample estimates:
## mean in group 0 mean in group 1 
##        30.41530        28.42382

Interpretations: The avarage number of the male passengers who died in Titanic was greater than the average number of the female passengers who died.