WFED540_Assignment#1
Woongbae Park
September 17, 2015
require(datasets)
require(ggvis)## Loading required package: ggvisrequire(dplyr)## Loading required package: dplyr
##
## Attaching package: 'dplyr'
##
## The following objects are masked from 'package:stats':
##
## filter, lag
##
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionrequire(magrittr)## Loading required package: magrittrrequire(xtable)## Loading required package: xtablerequire(htmlTable)## Loading required package: htmlTable
1. Read a .csv file containing data elements about Titanic travelers from http://www.personal.psu.edu/dlp/w540/datasets/titanicsurvival.csv into an R dataset. These data might be available in other locations, but you must read this .csv file from the source provided here. This dataset contains four variables and has no missing data-
*Read data from web
titanic <- read.csv (file="http://www.personal.psu.edu/dlp/w540/datasets/titanicsurvival.csv", header = TRUE, sep=",")
titan1 <-tbl_df(titanic)
titan1## Source: local data frame [2,201 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...htmlTable(head(titanic))| Class | Age | Sex | Survive | |
|---|---|---|---|---|
| 1 | 1 | 1 | 1 | 1 |
| 2 | 1 | 1 | 1 | 1 |
| 3 | 1 | 1 | 1 | 1 |
| 4 | 1 | 1 | 1 | 1 |
| 5 | 1 | 1 | 1 | 1 |
| 6 | 1 | 1 | 1 | 1 |
*filter Class/Age/Sex/Survive
crew <- filter(titan1, Class == 0)
crew## Source: local data frame [885 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 1 1
## 2 0 1 1 1
## 3 0 1 1 1
## 4 0 1 1 1
## 5 0 1 1 1
## 6 0 1 1 1
## 7 0 1 1 1
## 8 0 1 1 1
## 9 0 1 1 1
## 10 0 1 1 1
## .. ... ... ... ...glimpse(crew)## Observations: 885
## Variables: 4
## $ Class (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(crew)## Class Age Sex Survive
## Min. :0 Min. :1 Min. :0.000 Min. :0.0000
## 1st Qu.:0 1st Qu.:1 1st Qu.:1.000 1st Qu.:0.0000
## Median :0 Median :1 Median :1.000 Median :0.0000
## Mean :0 Mean :1 Mean :0.974 Mean :0.2395
## 3rd Qu.:0 3rd Qu.:1 3rd Qu.:1.000 3rd Qu.:0.0000
## Max. :0 Max. :1 Max. :1.000 Max. :1.0000firstclass <- filter(titan1, Class == 1)
firstclass## Source: local data frame [325 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...glimpse(firstclass)## Observations: 325
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(firstclass)## Class Age Sex Survive
## Min. :1 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:1 1st Qu.:1.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1 Median :1.0000 Median :1.0000 Median :1.0000
## Mean :1 Mean :0.9815 Mean :0.5538 Mean :0.6246
## 3rd Qu.:1 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1 Max. :1.0000 Max. :1.0000 Max. :1.0000secondclass <- filter(titan1, Class == 2)
secondclass## Source: local data frame [285 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 1 1
## 2 2 1 1 1
## 3 2 1 1 1
## 4 2 1 1 1
## 5 2 1 1 1
## 6 2 1 1 1
## 7 2 1 1 1
## 8 2 1 1 1
## 9 2 1 1 1
## 10 2 1 1 1
## .. ... ... ... ...glimpse(secondclass)## Observations: 285
## Variables: 4
## $ Class (int) 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, ...summary(secondclass)## Class Age Sex Survive
## Min. :2 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:2 1st Qu.:1.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :2 Median :1.0000 Median :1.0000 Median :0.000
## Mean :2 Mean :0.9158 Mean :0.6281 Mean :0.414
## 3rd Qu.:2 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.000
## Max. :2 Max. :1.0000 Max. :1.0000 Max. :1.000thirdclass <- filter(titan1, Class == 3)
thirdclass## Source: local data frame [706 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 1 1
## 2 3 1 1 1
## 3 3 1 1 1
## 4 3 1 1 1
## 5 3 1 1 1
## 6 3 1 1 1
## 7 3 1 1 1
## 8 3 1 1 1
## 9 3 1 1 1
## 10 3 1 1 1
## .. ... ... ... ...glimpse(thirdclass)## Observations: 706
## Variables: 4
## $ Class (int) 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(thirdclass)## Class Age Sex Survive
## Min. :3 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:3 1st Qu.:1.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :3 Median :1.0000 Median :1.0000 Median :0.0000
## Mean :3 Mean :0.8881 Mean :0.7224 Mean :0.2521
## 3rd Qu.:3 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :3 Max. :1.0000 Max. :1.0000 Max. :1.0000adult<- filter(titan1, Age == 1)
adult## Source: local data frame [2,092 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...glimpse(adult)## Observations: 2,092
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(adult)## Class Age Sex Survive
## Min. :0.000 Min. :1 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:1 1st Qu.:1.0000 1st Qu.:0.0000
## Median :1.000 Median :1 Median :1.0000 Median :0.0000
## Mean :1.301 Mean :1 Mean :0.7968 Mean :0.3126
## 3rd Qu.:3.000 3rd Qu.:1 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :3.000 Max. :1 Max. :1.0000 Max. :1.0000child<- filter(titan1, Age == 0)
child## Source: local data frame [109 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1
## 6 1 0 0 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## .. ... ... ... ...glimpse(child)## Observations: 109
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, ...
## $ Age (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ Sex (int) 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(child)## Class Age Sex Survive
## Min. :1.00 Min. :0 Min. :0.0000 Min. :0.0000
## 1st Qu.:2.00 1st Qu.:0 1st Qu.:0.0000 1st Qu.:0.0000
## Median :3.00 Median :0 Median :1.0000 Median :1.0000
## Mean :2.67 Mean :0 Mean :0.5872 Mean :0.5229
## 3rd Qu.:3.00 3rd Qu.:0 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :3.00 Max. :0 Max. :1.0000 Max. :1.0000male<- filter(titan1, Sex == 1)
male## Source: local data frame [1,731 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...glimpse(male)## Observations: 1,731
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(male)## Class Age Sex Survive
## Min. :0.000 Min. :0.000 Min. :1 Min. :0.000
## 1st Qu.:0.000 1st Qu.:1.000 1st Qu.:1 1st Qu.:0.000
## Median :1.000 Median :1.000 Median :1 Median :0.000
## Mean :1.195 Mean :0.963 Mean :1 Mean :0.212
## 3rd Qu.:3.000 3rd Qu.:1.000 3rd Qu.:1 3rd Qu.:0.000
## Max. :3.000 Max. :1.000 Max. :1 Max. :1.000female<- filter(titan1, Sex == 0)
female## Source: local data frame [470 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...glimpse(female)## Observations: 470
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(female)## Class Age Sex Survive
## Min. :0.000 Min. :0.0000 Min. :0 Min. :0.0000
## 1st Qu.:1.000 1st Qu.:1.0000 1st Qu.:0 1st Qu.:0.0000
## Median :2.000 Median :1.0000 Median :0 Median :1.0000
## Mean :2.011 Mean :0.9043 Mean :0 Mean :0.7319
## 3rd Qu.:3.000 3rd Qu.:1.0000 3rd Qu.:0 3rd Qu.:1.0000
## Max. :3.000 Max. :1.0000 Max. :0 Max. :1.0000survived<- filter(titan1, Survive == 1)
survived## Source: local data frame [711 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...glimpse(survived)## Observations: 711
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...summary(survived)## Class Age Sex Survive
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :1
## 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.:0.0000 1st Qu.:1
## Median :1.000 Median :1.0000 Median :1.0000 Median :1
## Mean :1.368 Mean :0.9198 Mean :0.5162 Mean :1
## 3rd Qu.:2.500 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1
## Max. :3.000 Max. :1.0000 Max. :1.0000 Max. :1died<- filter(titan1, Survive == 0)
died## Source: local data frame [1,490 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 0
## 2 1 1 1 0
## 3 1 1 1 0
## 4 1 1 1 0
## 5 1 1 1 0
## 6 1 1 1 0
## 7 1 1 1 0
## 8 1 1 1 0
## 9 1 1 1 0
## 10 1 1 1 0
## .. ... ... ... ...glimpse(died)## Observations: 1,490
## Variables: 4
## $ Class (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Age (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Sex (int) 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
## $ Survive (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...summary(died)## Class Age Sex Survive
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0
## 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.:1.0000 1st Qu.:0
## Median :1.000 Median :1.0000 Median :1.0000 Median :0
## Mean :1.369 Mean :0.9651 Mean :0.9154 Mean :0
## 3rd Qu.:3.000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0
## Max. :3.000 Max. :1.0000 Max. :1.0000 Max. :02. Calculate the total number of passengers in the dataset.
passangercrew <- filter(titan1, Class>=0)
passangercrew## Source: local data frame [2,201 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(passangercrew)## [1] 2201passangercrewNumber <- nrow(passangercrew)
passangercrewNumber## [1] 22013. Calculate the total proportion of passengers surviving.
spassangercrew <- filter(survived,Class>=0)
spassangercrew## Source: local data frame [711 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(spassangercrew)/nrow(titan1)## [1] 0.323035spassangercrewPortion <-nrow(spassangercrew)/nrow(titan1)
spassangercrewPortion ## [1] 0.3230354. Calculate the proportion of passengers surviving for each class of passenger.
- Survival rate of the crew members
crewspassanger <- filter(survived, Class==0)
crewspassanger## Source: local data frame [212 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 1 1
## 2 0 1 1 1
## 3 0 1 1 1
## 4 0 1 1 1
## 5 0 1 1 1
## 6 0 1 1 1
## 7 0 1 1 1
## 8 0 1 1 1
## 9 0 1 1 1
## 10 0 1 1 1
## .. ... ... ... ...nrow(crewspassanger)/nrow(crew)## [1] 0.239548crewspassangerPortion<-nrow(crewspassanger)/nrow(crew)
crewspassangerPortion## [1] 0.239548- Survival rate of the first class passengers
firstspassanger <- filter(survived, Class==1)
firstspassanger## Source: local data frame [203 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(firstspassanger)/nrow(firstclass)## [1] 0.6246154firstspassangerPortion<-nrow(firstspassanger)/nrow(firstclass)
firstspassangerPortion## [1] 0.6246154- Survival rate of the second class passengers
secondspassanger <- filter(survived, Class==2)
secondspassanger## Source: local data frame [118 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 1 1
## 2 2 1 1 1
## 3 2 1 1 1
## 4 2 1 1 1
## 5 2 1 1 1
## 6 2 1 1 1
## 7 2 1 1 1
## 8 2 1 1 1
## 9 2 1 1 1
## 10 2 1 1 1
## .. ... ... ... ...nrow(secondspassanger)/nrow(secondclass)## [1] 0.4140351secondspassangerPortion<-nrow(secondspassanger)/nrow(secondclass)
secondspassangerPortion## [1] 0.4140351- Survival rate of the third class passengers
thirdspassanger <- filter(survived, Class==3)
thirdspassanger## Source: local data frame [178 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 1 1
## 2 3 1 1 1
## 3 3 1 1 1
## 4 3 1 1 1
## 5 3 1 1 1
## 6 3 1 1 1
## 7 3 1 1 1
## 8 3 1 1 1
## 9 3 1 1 1
## 10 3 1 1 1
## .. ... ... ... ...nrow(thirdspassanger)/nrow(thirdclass)## [1] 0.2521246thirdspassangerPortion<-nrow(thirdspassanger)/nrow(thirdclass)
thirdspassangerPortion## [1] 0.25212465. Calculate the proportion of passengers surviving for each sex category. Which sex had the highest survival rate?
- Survival rate of male passengers
malespassanger <- filter(survived, Sex==1)
malespassanger## Source: local data frame [367 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(malespassanger)/nrow(male)## [1] 0.2120162- Survival rate of female passengers
femalespassanger <- filter(survived, Sex==0)
femalespassanger## Source: local data frame [344 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...nrow(femalespassanger)/nrow(female)## [1] 0.7319149summarise(group_by(female,Sex), survival_rate=nrow(malespassanger)/nrow(male) , nrow(femalespassanger)/nrow(female) ) ```
6. Calculate the proportion of passengers surviving for each age category. Which age had the lowest survival rate?
- Survival rate of adult passengers
adultspassanger <- filter(survived, Age==1)
adultspassanger## Source: local data frame [654 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(adultspassanger)/nrow(adult)## [1] 0.3126195- Survival rate of children
childspassanger <- filter(survived, Age==0)
childspassanger## Source: local data frame [57 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1
## 6 1 0 0 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## .. ... ... ... ...nrow(childspassanger)/nrow(child)## [1] 0.5229358summarise(group_by(child,Age), survival_rate=nrow(adultspassanger)/nrow(adult) , nrow(childspassanger)/nrow(child) )## Source: local data frame [1 x 3]
##
## Age survival_rate nrow(childspassanger)/nrow(child)
## (int) (dbl) (dbl)
## 1 0 0.3126195 0.52293587.Calculate the proportion of passengers surviving for each age/sex category (i.e., for adult males, child males, adult females, child females). Which group was most likely to survive? Least likely?
- Survival rate of adult male passenger
adultmale <-filter(titan1, Age==1, Sex==1)
adultmale## Source: local data frame [1,667 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...adultmalespassanger<-filter(survived, Age==1, Sex==1)
adultmalespassanger## Source: local data frame [338 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(adultmalespassanger)/nrow(adultmale)## [1] 0.2027594- Survival rate of male children
childmale <-filter(titan1, Age==0, Sex==1)
childmale## Source: local data frame [64 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1
## 6 2 0 1 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## .. ... ... ... ...childmalespassanger<-filter(survived, Age==0, Sex==1)
childmalespassanger## Source: local data frame [29 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1
## 6 2 0 1 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## .. ... ... ... ...nrow(childmalespassanger)/nrow(childmale)## [1] 0.453125- Survival rate of adult female passenger
adultfemale <-filter(titan1, Age==1, Sex==0)
adultfemale## Source: local data frame [425 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...adultfemalespassanger<-filter(survived, Age==1, Sex==0)
adultfemalespassanger## Source: local data frame [316 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...nrow(adultfemalespassanger)/nrow(adultfemale)## [1] 0.7435294- Survival rate of female children
childfemale <-filter(titan1, Age==0, Sex==0)
childfemale## Source: local data frame [45 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 0 1
## 2 2 0 0 1
## 3 2 0 0 1
## 4 2 0 0 1
## 5 2 0 0 1
## 6 2 0 0 1
## 7 2 0 0 1
## 8 2 0 0 1
## 9 2 0 0 1
## 10 2 0 0 1
## .. ... ... ... ...childfemalespassanger<-filter(survived, Age==0, Sex==0)
childfemalespassanger## Source: local data frame [28 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 0 1
## 2 2 0 0 1
## 3 2 0 0 1
## 4 2 0 0 1
## 5 2 0 0 1
## 6 2 0 0 1
## 7 2 0 0 1
## 8 2 0 0 1
## 9 2 0 0 1
## 10 2 0 0 1
## .. ... ... ... ...nrow(childfemalespassanger)/nrow(childfemale)## [1] 0.6222222Survival Rate
- Adult female passenger
nrow(adultfemalespassanger)/nrow(adultfemale)## [1] 0.7435294- Female children
nrow(childfemalespassanger)/nrow(childfemale)## [1] 0.6222222- Male children
nrow(childmalespassanger)/nrow(childmale)## [1] 0.453125- Adult male passenger
nrow(adultmalespassanger)/nrow(adultmale)## [1] 0.20275948. Calculate the proportion of passengers surviving for each age/sex/class category. Which group had the highest mortality in this disaster. Why?
nrow(firstspassanger)/nrow(firstclass)## [1] 0.6246154firstadultmale <-filter(titan1, Class==1, Age==1, Sex==1)
firstadultmale## Source: local data frame [175 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...firstadultmalespassanger<-filter(survived,Class==1, Age==1, Sex==1)
firstadultmalespassanger## Source: local data frame [57 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 1 1
## 2 1 1 1 1
## 3 1 1 1 1
## 4 1 1 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## 7 1 1 1 1
## 8 1 1 1 1
## 9 1 1 1 1
## 10 1 1 1 1
## .. ... ... ... ...nrow(firstadultmalespassanger)/nrow(firstadultmale)## [1] 0.3257143firstchildmale <-filter(titan1, Class==1,Age==0, Sex==1)
firstchildmale## Source: local data frame [5 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1firstchildmalespassanger<-filter(survived, Class==1, Age==0, Sex==1)
firstchildmalespassanger## Source: local data frame [5 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 1 1
## 2 1 0 1 1
## 3 1 0 1 1
## 4 1 0 1 1
## 5 1 0 1 1nrow(firstchildmalespassanger)/nrow(firstchildmale)## [1] 1firstadultfemale <-filter(titan1, Class==1,Age==1, Sex==0)
firstadultfemale## Source: local data frame [144 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...firstadultfemalespassanger<-filter(survived,Class==1, Age==1, Sex==0)
firstadultfemalespassanger## Source: local data frame [140 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 1 0 1
## 2 1 1 0 1
## 3 1 1 0 1
## 4 1 1 0 1
## 5 1 1 0 1
## 6 1 1 0 1
## 7 1 1 0 1
## 8 1 1 0 1
## 9 1 1 0 1
## 10 1 1 0 1
## .. ... ... ... ...nrow(firstadultfemalespassanger)/nrow(firstadultfemale)## [1] 0.9722222firstchildfemale <-filter(titan1, Class==1,Age==0, Sex==0)
firstchildfemale## Source: local data frame [1 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 0 1firstchildfemalespassanger<-filter(survived, Class==1,Age==0, Sex==0)
firstchildfemalespassanger## Source: local data frame [1 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 1 0 0 1nrow(firstchildfemalespassanger)/nrow(firstchildfemale)## [1] 1nrow(secondspassanger)/nrow(secondclass)## [1] 0.4140351secondadultmale <-filter(titan1, Class==2, Age==1, Sex==1)
secondadultmale## Source: local data frame [168 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 1 1
## 2 2 1 1 1
## 3 2 1 1 1
## 4 2 1 1 1
## 5 2 1 1 1
## 6 2 1 1 1
## 7 2 1 1 1
## 8 2 1 1 1
## 9 2 1 1 1
## 10 2 1 1 1
## .. ... ... ... ...secondadultmalespassanger<-filter(survived,Class==2, Age==1, Sex==1)
secondadultmalespassanger## Source: local data frame [14 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 1 1
## 2 2 1 1 1
## 3 2 1 1 1
## 4 2 1 1 1
## 5 2 1 1 1
## 6 2 1 1 1
## 7 2 1 1 1
## 8 2 1 1 1
## 9 2 1 1 1
## 10 2 1 1 1
## 11 2 1 1 1
## 12 2 1 1 1
## 13 2 1 1 1
## 14 2 1 1 1nrow(secondadultmalespassanger)/nrow(secondadultmale)## [1] 0.08333333secondchildmale <-filter(titan1, Class==2,Age==0, Sex==1)
secondchildmale## Source: local data frame [11 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 0 1 1
## 2 2 0 1 1
## 3 2 0 1 1
## 4 2 0 1 1
## 5 2 0 1 1
## 6 2 0 1 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## 11 2 0 1 1secondchildmalespassanger<-filter(survived, Class==2, Age==0, Sex==1)
secondchildmalespassanger## Source: local data frame [11 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 0 1 1
## 2 2 0 1 1
## 3 2 0 1 1
## 4 2 0 1 1
## 5 2 0 1 1
## 6 2 0 1 1
## 7 2 0 1 1
## 8 2 0 1 1
## 9 2 0 1 1
## 10 2 0 1 1
## 11 2 0 1 1nrow(secondchildmalespassanger)/nrow(secondchildmale)## [1] 1secondadultfemale <-filter(titan1, Class==2,Age==1, Sex==0)
secondadultfemale## Source: local data frame [93 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 0 1
## 2 2 1 0 1
## 3 2 1 0 1
## 4 2 1 0 1
## 5 2 1 0 1
## 6 2 1 0 1
## 7 2 1 0 1
## 8 2 1 0 1
## 9 2 1 0 1
## 10 2 1 0 1
## .. ... ... ... ...secondadultfemalespassanger<-filter(survived,Class==2, Age==1, Sex==0)
secondadultfemalespassanger## Source: local data frame [80 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 1 0 1
## 2 2 1 0 1
## 3 2 1 0 1
## 4 2 1 0 1
## 5 2 1 0 1
## 6 2 1 0 1
## 7 2 1 0 1
## 8 2 1 0 1
## 9 2 1 0 1
## 10 2 1 0 1
## .. ... ... ... ...nrow(secondadultfemalespassanger)/nrow(secondadultfemale)## [1] 0.8602151secondchildfemale <-filter(titan1, Class==2,Age==0, Sex==0)
secondchildfemale## Source: local data frame [13 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 0 0 1
## 2 2 0 0 1
## 3 2 0 0 1
## 4 2 0 0 1
## 5 2 0 0 1
## 6 2 0 0 1
## 7 2 0 0 1
## 8 2 0 0 1
## 9 2 0 0 1
## 10 2 0 0 1
## 11 2 0 0 1
## 12 2 0 0 1
## 13 2 0 0 1secondchildfemalespassanger<-filter(survived, Class==2,Age==0, Sex==0)
secondchildfemalespassanger## Source: local data frame [13 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 2 0 0 1
## 2 2 0 0 1
## 3 2 0 0 1
## 4 2 0 0 1
## 5 2 0 0 1
## 6 2 0 0 1
## 7 2 0 0 1
## 8 2 0 0 1
## 9 2 0 0 1
## 10 2 0 0 1
## 11 2 0 0 1
## 12 2 0 0 1
## 13 2 0 0 1nrow(secondchildfemalespassanger)/nrow(secondchildfemale)## [1] 1nrow(thirdspassanger)/nrow(thirdclass)## [1] 0.2521246thirdadultmale <-filter(titan1, Class==3, Age==1, Sex==1)
thirdadultmale## Source: local data frame [462 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 1 1
## 2 3 1 1 1
## 3 3 1 1 1
## 4 3 1 1 1
## 5 3 1 1 1
## 6 3 1 1 1
## 7 3 1 1 1
## 8 3 1 1 1
## 9 3 1 1 1
## 10 3 1 1 1
## .. ... ... ... ...thirdadultmalespassanger<-filter(survived,Class==3, Age==1, Sex==1)
thirdadultmalespassanger## Source: local data frame [75 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 1 1
## 2 3 1 1 1
## 3 3 1 1 1
## 4 3 1 1 1
## 5 3 1 1 1
## 6 3 1 1 1
## 7 3 1 1 1
## 8 3 1 1 1
## 9 3 1 1 1
## 10 3 1 1 1
## .. ... ... ... ...nrow(thirdadultmalespassanger)/nrow(thirdadultmale)## [1] 0.1623377thirdchildmale <-filter(titan1, Class==3,Age==0, Sex==1)
thirdchildmale## Source: local data frame [48 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 0 1 1
## 2 3 0 1 1
## 3 3 0 1 1
## 4 3 0 1 1
## 5 3 0 1 1
## 6 3 0 1 1
## 7 3 0 1 1
## 8 3 0 1 1
## 9 3 0 1 1
## 10 3 0 1 1
## .. ... ... ... ...thirdchildmalespassanger<-filter(survived, Class==3, Age==0, Sex==1)
thirdchildmalespassanger## Source: local data frame [13 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 0 1 1
## 2 3 0 1 1
## 3 3 0 1 1
## 4 3 0 1 1
## 5 3 0 1 1
## 6 3 0 1 1
## 7 3 0 1 1
## 8 3 0 1 1
## 9 3 0 1 1
## 10 3 0 1 1
## 11 3 0 1 1
## 12 3 0 1 1
## 13 3 0 1 1nrow(thirdchildmalespassanger)/nrow(thirdchildmale)## [1] 0.2708333thirdadultfemale <-filter(titan1, Class==3,Age==1, Sex==0)
thirdadultfemale## Source: local data frame [165 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 0 1
## 2 3 1 0 1
## 3 3 1 0 1
## 4 3 1 0 1
## 5 3 1 0 1
## 6 3 1 0 1
## 7 3 1 0 1
## 8 3 1 0 1
## 9 3 1 0 1
## 10 3 1 0 1
## .. ... ... ... ...thirdadultfemalespassanger<-filter(survived,Class==3, Age==1, Sex==0)
thirdadultfemalespassanger## Source: local data frame [76 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 1 0 1
## 2 3 1 0 1
## 3 3 1 0 1
## 4 3 1 0 1
## 5 3 1 0 1
## 6 3 1 0 1
## 7 3 1 0 1
## 8 3 1 0 1
## 9 3 1 0 1
## 10 3 1 0 1
## .. ... ... ... ...nrow(thirdadultfemalespassanger)/nrow(thirdadultfemale)## [1] 0.4606061thirdchildfemale <-filter(titan1, Class==3,Age==0, Sex==0)
thirdchildfemale## Source: local data frame [31 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 0 0 1
## 2 3 0 0 1
## 3 3 0 0 1
## 4 3 0 0 1
## 5 3 0 0 1
## 6 3 0 0 1
## 7 3 0 0 1
## 8 3 0 0 1
## 9 3 0 0 1
## 10 3 0 0 1
## .. ... ... ... ...thirdchildfemalespassanger<-filter(survived, Class==3,Age==0, Sex==0)
thirdchildfemalespassanger## Source: local data frame [14 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 3 0 0 1
## 2 3 0 0 1
## 3 3 0 0 1
## 4 3 0 0 1
## 5 3 0 0 1
## 6 3 0 0 1
## 7 3 0 0 1
## 8 3 0 0 1
## 9 3 0 0 1
## 10 3 0 0 1
## 11 3 0 0 1
## 12 3 0 0 1
## 13 3 0 0 1
## 14 3 0 0 1nrow(thirdchildfemalespassanger)/nrow(thirdchildfemale)## [1] 0.4516129nrow(crewspassanger)/nrow(crew)## [1] 0.239548crewadultmale <-filter(titan1, Class==0, Age==1, Sex==1)
crewadultmale## Source: local data frame [862 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 1 1
## 2 0 1 1 1
## 3 0 1 1 1
## 4 0 1 1 1
## 5 0 1 1 1
## 6 0 1 1 1
## 7 0 1 1 1
## 8 0 1 1 1
## 9 0 1 1 1
## 10 0 1 1 1
## .. ... ... ... ...crewadultmalespassanger<-filter(survived,Class==0,Age==1,Sex==1)
crewadultmalespassanger## Source: local data frame [192 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 1 1
## 2 0 1 1 1
## 3 0 1 1 1
## 4 0 1 1 1
## 5 0 1 1 1
## 6 0 1 1 1
## 7 0 1 1 1
## 8 0 1 1 1
## 9 0 1 1 1
## 10 0 1 1 1
## .. ... ... ... ...nrow(crewadultmalespassanger)/nrow(crewadultmale)## [1] 0.2227378crewadultfemale <-filter(titan1, Class==0,Age==1, Sex==0)
crewadultfemale## Source: local data frame [23 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 0 1
## 2 0 1 0 1
## 3 0 1 0 1
## 4 0 1 0 1
## 5 0 1 0 1
## 6 0 1 0 1
## 7 0 1 0 1
## 8 0 1 0 1
## 9 0 1 0 1
## 10 0 1 0 1
## .. ... ... ... ...crewadultfemalespassanger<-filter(survived,Class==0, Age==1, Sex==0)
crewadultfemalespassanger## Source: local data frame [20 x 4]
##
## Class Age Sex Survive
## (int) (int) (int) (int)
## 1 0 1 0 1
## 2 0 1 0 1
## 3 0 1 0 1
## 4 0 1 0 1
## 5 0 1 0 1
## 6 0 1 0 1
## 7 0 1 0 1
## 8 0 1 0 1
## 9 0 1 0 1
## 10 0 1 0 1
## 11 0 1 0 1
## 12 0 1 0 1
## 13 0 1 0 1
## 14 0 1 0 1
## 15 0 1 0 1
## 16 0 1 0 1
## 17 0 1 0 1
## 18 0 1 0 1
## 19 0 1 0 1
## 20 0 1 0 1nrow(crewadultfemalespassanger)/nrow(crewadultfemale)## [1] 0.86956529. Write a summary of your findings. Your summary may contain no more than 60 words.
Survival rate by groups
*1-1 Second Class Child Female:100.00%(13/13).
*1-2. Second Class Child Male: 100.00%(11/11).
*1-3. First Class Child Male: 100.00%(5/5).
*1-4. First Class Child Female: 100.00%(1/1).
*5. First Class Adult Female: 97.22% (140/144).
*6. Crew Adult Female: 86.96% (20/23).
*7. Second Class Adult Female: 86.02%(80/93).
*8. Third Class Adult Female: 46.06%(76/165).
*9. Third Class ChildFemale:45.16% (14/31).
*10. First Class Adult Male: 32.57% (57/175).
*11. Third Class Child Male: 27.08% (13/48).
*12. Crew Adult Male: 22.27% (192/862).
*13. Third Class Adult Male: 16.23% (75/462).
*14. Second Class Adult Male: 8.33% (14/168).
My major finding is that the survival rate for passengers on the Titanic depends on three parameters: class, age and sex. In order to compare the survival rates, passengers were divided into fourteen groups based on the three parameters above. The survival rate of first and second class children(male, female) is 100%. However, the sample number is too small. The sample only includes 13 second class female children, 11 second class male children , 5 first class male children and 1 first class female children. Among the groups whose sample number is larger than 20, the first class adult female survival rate is the highest (97.22%). The adult female crew members have the second highest survival rate (86.96%). The second class adult females have the third highest survival rate (86.02%). All the other groups’ survival rate is less than 50%. The groups with the lowest survival rates are as follows: the second class adult males (8.33%) , the third class adult males (16.23%), and adult male crew members (22.27%). Overall, from these statistics, I deduced that children and females were saved primarily. Nevertheless, it was possible that children and females in the third class were pushed back on the priority relief list. Among the adult male group, the firs class adult males’ survival rate is relatively higher than any other male adult group. (32.57%) From the fact, I inferred that the first class male adult passengers were considered priority number two right after children and females.