Titanic1
Om Joy Halder
26-09-2017
Q1a: How many passengers were on board the Titanic?
Q1b. How many passengers survived the sinking of the Titanic?
Q1c. Create a one-way contingency table summarizing the Titanic passengers based on how many survived and how many died.
Q1d. What was the percentage of passengers who survived the sinking of the Titanic?
Q2a. Create a two-way contingency table characterising the passengers based on survival and based on the passenger class.
Q2b. Visualize your table using a Bar plot
barplot(mytable2,
main="Survival by Passenger Class",
xlab="Passenger Class", ylab="Frequency",
col=c("grey", "blue"), beside = TRUE)
legend("topleft", fill=c("grey", "blue"), legend=c("Died", "Survived"))
Q2c. How many first-class passengers survived the sinking of the Titanic?
Q2d. What was the percentage of first-class passengers who survived the sinking of the Titanic?
Q3a. Create a three-way contingency table showing the number of passengers based on the passenger's class, gender and survival.
Q3b. Express Q3a. in percentages, displaying answers up to two decimal places.
Visualize your table in Q3b, using a bar plot..
f <- xtabs(~ Survived+ Pclass, data=subset(Titanic, Sex == "female"))
m <- xtabs(~ Survived+ Pclass, data=subset(Titanic, Sex == "male"))
par(mfrow=c(1,2))
barplot(f,
main="Female", ylim = c(0,400),
xlab="Passenger Class", ylab="No of passengers",
col=c("grey", "blue"), beside = TRUE)
legend("topleft", fill=c("grey", "blue"), legend=c("Died", "Survived"))
barplot(m,
main="Male", ylim = c(0,400),
xlab="Passenger Class", ylab="No of passengers",
col=c("grey", "blue"), beside = TRUE)
legend("topleft", fill=c("grey", "blue"), legend=c("Died", "Survived"))
Q3c. How many Females traveling by First-Class survived the sinking of the Titanic?
Q3d. What was the percentage of survivors who were female?
C2.Visualize your answer in Q3d using a Pie-chart.
survived <- xtabs(~ Sex, data=subset(Titanic, Survived == 1))
pct <- c (round(prop.table(survived)*100,2))
lbls <- c("Female", "Male")
lbls <- paste(lbls, pct)
lbls <- paste(lbls,"%",sep="")
pie(survived, labels = lbls, col = c("blue","grey"), main = "Who survived?")
Q3e. What was the percentage of females on board the Titanic who survived?
Visualize your answer in Q3e using a Pie-chart.
female <- xtabs(~ Survived, data=subset(Titanic, Sex == "female"))
pct <- c (round(prop.table(female)*100,2))
lbls <- c("Died", "Survived")
lbls <- paste(lbls, pct)
lbls <- paste(lbls,"%",sep="")
pie(female, labels = lbls, col = c("red","blue"), main = "Percentage of females on board the Titanic who survived")
Q4a. Use a Pearson's Chi-squared test to evaluate whether the proportion of females who survived was larger than the proportion of males who survived?
Q4b.Create a Mosaic Plot of Titanic survivors and nonsurvivors based on gender (male/female), passenger class (First/Second/Third)
library(vcd)
mytable3 <- xtabs(~ Pclass+Sex+Survived, data=Titanic)
mosaic(data=mytable3,~ Pclass+Sex+Survived, shade=TRUE, legend = TRUE, main = "Mosaic Plot")
Q5a. Create a one-way contingency table showing the average age of the survivors and the average age of those who died
Q5b Create two boxplots, placed side-by-side, to visualize the distribution of the age of the survivors and the age of those who died.
boxplot( Age ~ Survived, data = Titanic, main = "Distribution of the age of the survivors ", xlab = "Survived?", ylab = "Age", col = "lightblue")
