Introduction to R

TP 4: Introduction to probabilities

Prof. Patrick Meyer

BioSys Lab - Université de Liège

Data.frame

• Ex 1 - 2 - 3

    data(CO2)
    data1 <- CO2[,-c(2,3)]
    data1 <- data.frame(data1,id=1:NROW(data1))
    data1 <- data1[order(data1$uptake),]
    
    data2 <- CO2[,-c(4,5)]
    data2 <- data.frame(data2,id=1:NROW(data1))
    names(data2) <- c("Plant","origin","change","number")
    
    write.table(data1,"data1.txt",sep=",")
    write.table(data2,"data2.txt",sep=" ")
  

  
  Explication:
  
  
• Ex 4 - 5 - 6

    rm(list=ls())
    data1 <- read.table("data1.txt",header=T,sep=",")
    data2 <- read.table("data2.txt",header=T,sep=" ")
    myCO2 <- merge(data1,data2,by.x="id",by.y="number")
    myCO2 <- myCO2[,-c(1,5)] 
  

  
  Explication:
  
  Complement:
  

table

•   table(z)["non","oui"]/sum(table(z))
    table(z)["oui","oui"]/sum(table(z)[,"oui"])
    sum(table(z)[,"oui"])/sum(table(z))
  

  
  Explication:
  
  
  

sample

•   set.seed(100)
    light <- sample(c("low","mid","high"),200,replace=T,prob=c(1/3,1/3,1/3))
    temp <- sample(c("low","mid","high"),200,replace=T,prob=c(1/3,1/3,1/3))
    pressure <- sample(c("low","mid","high"),200,replace=T,prob=c(1/3,1/3,1/3))
    mydata <- data.frame(light,temp,pressure)
    table(mydata)["high","high","high"]
  

  
  Explication:
  
  
  

Bayes

• 50%
  
  Explication: