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Introduction

The topic of this project is to find what social factors may have an effect on survival during maritime disasters. What would be a reason one group is more likely to survive than another group, this is what the project is about. Finding out how social norms predict the outcomes of disasters, in this project particularly maritime disasters. This topic is an interesting analysis to do because it explain to use what reason people survive and don’t survive. This information could be used to contribute to our knowledge and understanding of sociological issues because it shows the ways that society operates during disasters. It explains, if everyone is out to help themselves only, or if they actual want to help other people. If people do chose to help other people, this information can be helpful in showing who they chose to help.

Background

It is important when looking through this type of data to find as much information as you can. The individual data shows an abundance of information for the ships, but it also helpful to look at the ships data set because you get to compare variables and traits directly with all the ships. You get to see the data as a whole instead of just each individual ship. Also, you get to see what data may be important to focus on. The ship data gives us important information but the information given in the individual ships data is a lot more specific. Also, each ship has data that is unique to only that ship.

My Ship History and Details

The SS Norge was a Danish passenger ship that was carrying emigrants to New York. The ship set sail in June of 1904. There was 71 crew members, 9 second class, and 694 steerage passengers. In total the ship had 727 passengers. Steerage passengers meaning, travelers who did not have enough money to travel on the deck. Steerage was in cargo spaces, the tickets were cheap. Mainly poor immigrants traveled this way. The ship collided with a rock near Rockall. Rockall is within an exclusive economic zone the UK. The collision ripped holes in the ship’s hull where water began to flood. Many passengers jumped overboard but either drowned or pulled under by the suction of the sinking ship. It took the ship twelve minutes to sink. There were 160 survivors. The titanic had collided with an iceberg. It had 1317 passengers on the ship, which was almost two times as much as the SS Norge had. It took the titanic two hours and forty minutes to sink. Which is a significant time difference. The titanic had about 705 survivors.

My Ship Compared to Other Ships in the Disaster Data

My ship compared to the other ships is from first look similar. Many of the attributes of my ship coinside with the other ships. For example , the SS Norge had about half as many passengers as the RMS Titanic did. The graph below shows the SS Norge in the middle when it comes to the amount of passengers each ship had. The SS Norge land basically in the middle of all the other ships. My ship is close to the median of amount of passengers for all of the ships. The median of all of the ships is 733 while the total amount of passengers on the SS Norge was 727 passengers. Another variable that stuck out in these sets of data is cause, many of the ships had the same cause. There were ome ships whose cause was unique because not many or none of the other ships had the same cause.The cause for my ship was collision, and this was the most common out of the causes for all of the ships. What was unique is that one ships cause was being torpedoed.

median(ships$`No. of passengers`,na.rm = FALSE)
## [1] 733
plot1<-ggplot(ships, aes(y=`Name of Ship` , x=`No. of passengers` ))

title1<-ggtitle("Number of Passengers")

plot2<-ggplot(ships,aes(y=reorder(`Name of Ship`, `No. of passengers`) , x=`No. of passengers` ))
plot2 + title1 + geom_point()

```

plot3<-ggplot(ships,aes(x=`Cause`, y=`No. of passengers`))

plot3 +geom_boxplot()

Theory and Hypotheses

According to, Mikael Elinder and Oscar Erixson (2012) “When a ship sinks quickly, human actions are driven by hormonal reactions, such as a rapid increase of adrenaline, and selfish behavior should dominate.” This idea would show the sociological influence that when disasters are happening it is “every man for himself.” Also there is sociological representatives that crew members may have higher survival rates. To society men are expected to help people in emergencies. “However, crew members are familiar with the ship, often have emergency training, and are likely to receive early information about the severity of the situation. We, therefore, expect the crew to have a relative survival advantage if they try to save themselves rather than assisting the passengers” (Elinder and Erixson 2012). It makes sense that crew members would have a better survival advantage because they know more about the ship. Even though crew members are technically supposed to help passengers off the ship, it would not be surprising if crew members were to act for themselves. I hypothesize that crew members are more likely to survive than third class passengers. Also, I hypothesize that women are more likely to survive than men. First class members will have a higher chance of survival compared to third class. I hypothesize that women and children first will not be relevant for this information. Also, I hypothesize that the amount of time a ship sunk will have an impact on the urvival rate. Also, gender will have an affect, being male will be a positive factor in survival.

Data

“The data reported in this paper are available in Dataset S1.”(Elinder and Erixson 2012) Proceedings of the national Academy of Science. http://www.pnas.org/content/suppl/2012/07/24/1207156109.DCSupplemental/sd01.xlsx The data available for the SS Norge includes the amount of people who survived. Whether each passengers was male or female. If there were children on the ship. The data shows how many crew members were on the ship. Also, it shows what class each passenger was traveling. The data shows the nationality of the traveler and the cause. The variables for the SS Norge include, gender, passenger class, age, child and crew. Gender is measured by 1 meaning the passenger is a female and 0 being male. Age is measured by the actual number for the passenger’s age. Crew is measured by 1 being crew and 0 being not crew. Passenger class is measured by first class being 1, second class being 2 and third class being 3. Survival is measured by 0 meaning did not survive and 1 meaning survived. The first table shows how many passengers were female and how many were male, 373 were female and 422 were male. The second tabe shows how many passengers were crew and how many were not crew, 6 were crew and 727 were not crew. The third tabe shows hw many people survived and how many did not survive, 160 people survived and 635 did not survive. The third table shows how many passengers were in each passenger class. For the ships data when it comes to Women and children first, the data set shows that out of 18 ships only 5 of them ended up following women and children first. The last table shows out f the ships data set how many ships followed the women and children first protocol.

table(SS_Norge$Gender)
## 
##   0   1 
## 422 373
table(SS_Norge$Crew)
## 
##   0   1 
## 727  68
table(SS_Norge$Survival)
## 
##   0   1 
## 635 160
table(ships$`Women and children first`)
## 
##  0  1 
## 13  5

Results

The first table shows the relationship between survival and being a crew member. The table shows that 23 crew members srvived and 45 crew memebers did not survive out of the total number of crew members which was 65. The second table shows the relationship between survival and gender. This tabe shows that 123 men survived and only 37 women survived. The third table shows the relationship between passenger class and survival. Third class had highest number of passengers who survived. The last graph is a scatterplot showing the relationhip between the female passenger and male passengers comparing the titanic and all of the other ships. the Titanic is on the complete outside in this graph. They have the highest number of males on their ship. This is important to look at because the Titanic is a ship that carried out women and children first.

crosstab(SS_Norge, col.vars = "Crew",row.vars= "Survival", type = "f")
##         NA   NA  NA  NA  NA
## 1          Crew   0   1 Sum
## 2 Survival                 
## 3 0             590  45 635
## 4 1             137  23 160
## 5 Sum           727  68 795
crosstab(SS_Norge, col.vars = "Gender",row.vars= "Survival", type = "f")
##         NA     NA  NA  NA  NA
## 1          Gender   0   1 Sum
## 2 Survival                   
## 3 0               299 336 635
## 4 1               123  37 160
## 5 Sum             422 373 795
crosstab(SS_Norge, col.vars = "Passenger Class",row.vars= "Survival", type = "f")
##         NA              NA  NA  NA  NA    NA  NA
## 1          Passenger Class   1   2   3 loose Sum
## 2 Survival                                      
## 3 0                          1   9 576     4 590
## 4 1                          0   0 135     2 137
## 5 Sum                        1   9 711     6 727
plot5<-ggplot(ships, aes(x=`Name of Ship` , y=`prop_survival` ))

plot5 + geom_bar(stat="identity")

plot5 +geom_bar(stat="identity") +theme(axis.text.x =element_text(angle = 90))

Conclusions and Future Research

Overall my study shows that social norm of women and children being first to save in disasters may not be true. It may be that every person is out to help themsleves. Self preservaion may be the social norm that factored in to this event. Everyone may have been scared and just trying to save themself. Especially with only 12 minutes to even think about what to do, our frst instinct as human beings is to help ourselves. More data could be what were the ways that people survived, also where people were at on the ship that had survival. Certain areas on the ship could be easier to survive from. Maybe if you are at the bottom of the ship and the ship is sinking your survival chances are lower. For further research there could be data collected for maritime disasters that have happened more recntly if there are any. Also, you can compare maritime disasters to other disasters to see if women and children first is common to other disaters but not maritime or is it exclusive to most disasters.

GLM

results<-glm(Survival~Gender + Crew, data=SS_Norge, family = binomial(link = logit))
coef(results)
## (Intercept)      Gender        Crew 
##  -0.9364366  -1.2715249   0.2935370
results<-glm(Survival~`Passenger Class`, data=SS_Norge, family = binomial(link = logit))
coef(results)
##            (Intercept)     `Passenger Class`2     `Passenger Class`3 
##          -1.556607e+01           1.196291e-08           1.411524e+01 
## `Passenger Class`loose 
##           1.487292e+01

This GLM table shows if a certain varibale has a positive affect on survival rate or a negatv affect on survival rate. In this table it shows that gender has a negative affect on survival. This means that being female has a negative affect on survival and that men have a better chance of survival. Als, this table shows that third passenger class has the most positive affect on survival. This table also shows that being a crew member has a positive afect on survival but it is not a particularly high chance of survival. This can be due to the fact that on the SS Norge there were only 65 crew members. There were two female Crew members and they both did not survive, being a female crew member did not increase your chances of survival. Being male and in the crew were factors that would increase you chances of survival. Being a third class male will increases your chance of survival. This was not my focus but the data does show this to be true with bulk of survivors coming from the third class. The data does not support any of my hypotheses. The data shows that women were not in favor to survive. The data shows that crew members did not hae a hgher survival rate than third class members. Lastly the data shows that being first class had a negative affect on survival on the SS Norge. The fndings of the Titanic were that women and children did have higher rates of survival. This can be because the Titanic had a lot more time before the ship sank, so men may have been more able to help. Also this could be because the captain may have called for women and children to be first.

References

Elinder, Mikael and Oscar Erixson. 2012. “Gender, social norms, and survival in maritime disasters.” PNAS 109(33):13220-13224.