• In this presentation, we are using the ‘Titanic’ dataset to determine to what extent age, sex, and the presence of family members are correlated with survival of the accident.
• In the evacuation process, the popular conception is that women and children were given the highest priority to board lifeboats
• Also, in the movie, Rose’s boyfriend is able to survive by pretending a little boy is his own
• Today we’re playing Mythbusters to see whether the data actually reflects this

## Warning: package 'ggplot2' was built under R version 4.0.4

## Warning: package 'plotly' was built under R version 4.0.4

• For the purposes of this project, assuming any passenger with indeterminate survival status to be dead/missing
• We will only be considering passengers with a given age (I omitted passengers w/ empty Age entries)
• The ship crew is not present in this dataset

• Keep in mind some passengers simply were better off because of which class they were traveling
• We will not be discussing the reasons for this, as this could be due to a large variety of factors that go beyond our given dataset
• However, the differing survival rates by class will be significant to our analysis

ggplot(first, aes(x = "", y = Alive, fill = Survived)) + 
  geom_bar(stat = "identity", width = 1) + coord_polar("y", start = 0) + 
  theme_void()

ggplot(second, aes(x = "", y = Alive, fill = Survived)) + 
  geom_bar(stat = "identity", width = 1) + coord_polar("y", start = 0) + 
  theme_void()

ggplot(third, aes(x = "", y = Alive, fill = Survived)) + 
  geom_bar(stat = "identity", width = 1) + coord_polar("y", start = 0) + 
  theme_void()

• Obviously, not looking good for male passengers
• Overall, female passengers had a survival rate of just over 50%, while male passengers’ likelihood for survival was under 15%
• However, this reflects data across all passenger classes

• Again, it is obvious that female passengers were favored in the evacuation regardless of class
• Despite fewer third-class passengers surviving across the board, women fared noticeably better, with 31% of female third-class passengers surviving as opposed to around 11% of males

## # A tibble: 2 x 2
##   Survived   Age
## *    <dbl> <dbl>
## 1        0  30.5
## 2        1  28.3

• The mean age of those passengers who survived is slightly younger than those who didn’t
• A 2.2 year age gap suggests a younger crowd made it off the Titanic safely, but does not immediately correlate age group with survival

## # A tibble: 2 x 4
##   AgeGroup Alive DeadMiss SurvPer
##   <chr>    <dbl>    <dbl>   <dbl>
## 1 Adult      229      663   0.257
## 2 Child       61       93   0.396

##   c_perc_survived c_perc_deadmiss
## 1       0.2103448       0.1230159

• Although more than 50% of children in this dataset are either dead or missing, their survival is still markedly better than adults’
• Perhaps even more revealing is the percentages of children among those who lived vs those who died

• Table for whether or not the survivors were with family

## HasFamily
## FALSE  TRUE 
##   130   160

• Another table for the dead and missing

## HasFamily
## FALSE  TRUE 
##   460   296

• Out of the survivors, more than half were with family members, while less than 40% of the dead and missing were traveling with family

• Numerically at least, the popular myths we set out to investigate all seem to hold some truth
• Although many still died in the disaster, it would seem women and children were favored in the evacuation process
• It also appears that passengers travelling with family members had a significantly better chance of survival than those who were not