.Rhistory
myvector <- c(10, 5, 9)
myvector
myvector <- c(123, 3, -2, myvecotr)
myvector <- c(123, 3, -2, myvector)
myvector
myvector <- c(123, 3, -2, (myvector)
myvector <- c(123, 3, -2, (myvector))
myvector
median (myvector)
v <- cc("cdcd", "dfddf")
v <- c("cdcd", "dfddf")
v
population <- 1:1000
population
sample(population, 10)
mean(sample(population, 10))
mean(sample(population, 10))
mean(sample(population, 10))
mean(population)
median(population)
mean(sample(population, 1000))
eyes< - c(2,3,5)
eyes <- c(2,3,5)
labels <- c("brown", "green","blue")
barplot(eyes, names.arg = labels, ylab = "Frenquecy")
barplot(eyes, xlab = "eyes color" = , ylab = "Frenquecy")
barplot(eyes, xlab = "eyes color" , ylab = "Frenquecy")
barplot(eyes, xlab = eyes , ylab = "Frenquecy")
sample
sample <- sample(population,100)
sample
boxplot(sample)
summary(sample)
samplesNum <- 10
samplsSize <- 20
samples <- matrix(,nrow = samplesNum, ncol = samplesSize)
samplesSize
samplesSize <- 20
samplesSize
samples <- matrix(,nrow = samplesNum, ncol = samplesSize)
boxplot(samples)
replicate(10,mean(sample(1:500, 10)))
createRandomSamples <- function(pop, num = 10, size = 10){}
createRandomSamples <- function(pop, num = 10, size = 10){replicate(num, sample(population, size))}
boxplot(createRandomSamples(size = 20))
rep(10,1)
rep(1,10)
population <- c(rep(0,10000), rep(1,10000))
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,1)
sample(population,10)
sample(population,10)
sample(population,10)
sum(sample(population,10))
sum(sample(population,10))
sum(sample(population,10))
sum(sample(population,10))
sum(sample(population,10))
sum(sample(population,10))
replicate(10,sum(sample(population,10)))
replicate(100,sum(sample(population,10)))
values <- replicate(10000,sum(sample(population,10)))
hist(values)
choose(10,3)
erros <- (0:10)
dbinom(errors, 10,.4)
dbinom(erros, 10,.4)
dbinom(6, 10,.4)
dbinom(0:10, 10,.4)
dunif(0.2)
curve(dunif(x))
curve(dunif(x), xlim = c(-1,1), ylim = c(0,1.5))
runif(10)
runif(10)
runif(10)
mean(runif(10))
mean(runif(1000000))
mean(runif(10000000000000000))
mean(runif(10000000000000))
mean(runif(10000000000))
mean(runif(10000000))
mean(runif(10000000))
rbinom(10,10,0.3)
rbinom(10000,10,0.3)
mean(rbinom(10000,10,0.3))
mean(rbinom(10000000,10,0.3))
source('E:/OnlineStudy_Framework/AnalysisScripts/1-read-and-calculate_errors_time_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/2-aggregate_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/2-aggregate_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/1-read-and-calculate_errors_time_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/2-aggregate_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/4-Abs-and-True-error-by-percent_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/1-read-and-calculate_errors_time_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/2-aggregate_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/4-Abs-and-True-error-by-percent_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/4-Abs-and-True-error-by-percent_1.R', echo=TRUE)
source('E:/OnlineStudy_Framework/AnalysisScripts/3a-analysis-errors_1.R', echo=TRUE)