gistfile1.txt

options(repr.plot.width=15)
analyse <- function(current_samples, p0) {
    # p0 = 0.5
    print("Current samples:")
    print(current_samples)

    proportion = sum(current_samples<(p0*n))
    print(paste("Proportion less than",p0*n,'is',proportion,"out of",length(current_samples)))

    binom_test_result = binom.test(proportion, length(current_samples), p=p0)
    print(binom_test_result)

    pvalues = c()
    means = c()
    for (i in 1:length(current_samples)){
        pval = binom.test(sum(current_samples[1:i]<(p0*n)), length(current_samples[1:i]), p=p0)$p.value
        pvalues = c(pvalues, pval)
        means = c(means, mean(current_samples[1:i]))
    }
    plot1 = qplot(x=1:length(current_samples), y=pvalues, geom='line', ylab='P-value', xlab='number',size=I(4))+geom_hline(colour='blue', yintercept=0.05)
    plot2 = qplot(x=1:length(current_samples), y=means, geom='line', ylab='Mean', xlab='number',size=I(4), ylim = c(0,100))+geom_hline(colour='red', yintercept=50)
    ggarrange(plot1, plot2, labels=c('A','B'))
}
theme_set(theme_bw() + theme(text = element_text(size = 25))   )
current_samples = c(62,55,45,15,41,24,16, 47,33,1, 63, 24, 55, 40, 44, 49, 2, 48,6,69)
analyse(current_samples, 0.5)