数学カフェ確率・統計・機械学習回「速習確率・統計」

$# p = 0.7 trial_size = 10000 sample_size = 30 set.seed(71) # gen_binom_var <- function() { return(sum(rbern(sample_size, p...$

$# n <- 10000; p <- 0.7; trial_size = 10000 width=10 # gen_binom_var <- function() { return(sum(rbern(n, p))) } result <- r...$

$# n <- 10000; p <- 0.7 trial_size = 30000 width=0.18 # gen_binom_var <- function() { return(sum(rbern(n, p))) } result <- ...$

$# p <- 0.7; n <- 1000; trial_size <- 100000; width <- 0.3; df <- 3 # (3 ) gen_binom_var <- function() { return(sum(rbern(n...$

$width <- 0.02 p <- 0.5; sample_size <- 1000 trial_size <- 100000 gen_unif_rand <- function() { # sample_size 2 # return (s...$

$a <- 5 b <- 8; width <- 0.05 p <- 0.5 sample_size <- 1000 trial_size <- 500000 gen_unif_rand <- function() { # sample_size...$

$width <- 0.03; p <- 0.5 digits_length <- 30; set_size <- 3 trial_size <- 30000 gen_unif_rand <- function() { # digits_leng...$