setwd("C:/Users/Internship")
titanic.df<-read.csv(paste("Titanic Data.csv", sep=""))
View(titanic.df)

Create a table showing the average age of the survivors and the average age of the people who died.

aggregate(titanic.df$Age, by=list(Age=titanic.df$Survived), mean)
##   Age        x
## 1   0 30.41530
## 2   1 28.42382

Since 1 represents survivors and 0 represents deceased, average age of the survivors=28.42382 average age of the people who died=30.41530.

Run a t-test to test the hypothesis:

The Titanic survivors were younger than the passengers who died.

Null Hypothesis: There is no significant age difference between the survivors and the passengers who died. Interpretation

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

Since p-value is 0.02949<0.05, the null hypothesis can be rejected. This implies there is a significant difference between the mean age of survivors and those people who died