You can also embed plots, for example:
### 2b. Importing the file ###
titanic <- read.csv(paste("Titanic Data.csv", sep=""))### 2b. Viewing the file ###
View(titanic)### 3a. To count total no.of passengers ###
total <- nrow(titanic)
total## [1] 889### 3b. number of survivers ###
surv <- table(titanic$Survived)
surv##
## 0 1
## 549 340### 3c. percentage of survivers ###
surv_per <- mean(titanic$Survived)*100
surv_per## [1] 38.24522### 3d.First-class survivers ###
surv_first <- xtabs(~Survived+Pclass, data=titanic)
surv_first## Pclass
## Survived 1 2 3
## 0 80 97 372
## 1 134 87 119### 3e. Percentage of first-class survivers ###
surv_first_per <- prop.table(table(titanic$Pclass, titanic$Survived),1)*100
surv_first_per##
## 0 1
## 1 37.38318 62.61682
## 2 52.71739 47.28261
## 3 75.76375 24.23625### 3f. No.of first class female survivers ###
surv_first_female <- table(titanic$Sex, titanic$Survive, titanic$Pclass)
surv_first_female## , , = 1
##
##
## 0 1
## female 3 89
## male 77 45
##
## , , = 2
##
##
## 0 1
## female 6 70
## male 91 17
##
## , , = 3
##
##
## 0 1
## female 72 72
## male 300 47### 3h. Percentage of female survivers ###
surv_female_onboard <- prop.table(table(titanic$Sex, titanic$Survive),1)*100
surv_female_onboard##
## 0 1
## female 25.96154 74.03846
## male 81.10919 18.89081### 3g. Percentage of survivors who are female ###
surv_female <- prop.table(xtabs(~Survived+Sex,data=titanic),1)*100
surv_female## Sex
## Survived female male
## 0 14.75410 85.24590
## 1 67.94118 32.05882### 3i. Chi sqaure test ###
mytable<-xtabs(~Survived+Sex,data=titanic)
addmargins(mytable)## Sex
## Survived female male Sum
## 0 81 468 549
## 1 231 109 340
## Sum 312 577 889chisq.test(mytable)##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: mytable
## X-squared = 258.43, df = 1, p-value < 2.2e-16