http://www.commres.net/ 2026-04-17T15:33:52+00:00 http://www.commres.net/ http://www.commres.net/_media/wiki/logo.png text/html 2025-11-02T23:10:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/head_first_statistics/estimating_populations_and_samples/mean_of_proportions_code?rev=1762125005&do=diff set.seed(101) k <- 1000 n <- 100 p <- 1/4 q <- 1-p # in order to clarify what we are doing # X~B(n,p) 일 때, 100개의 검볼을 샘플링해서 # red gumball을 세봤더니 rbinom(1,n,p) # 24개 였다라는 뜻 # 아래는 이것을 1000번 (k번) 한 것 numbers.of.red.gumball <- rbinom(k, n, p) head(numbers.of.red.gumball) # 아래처럼 n으로 (100개의 검볼이 총 숫자이므로) # 나눠주면 비율을 구할 수 있다 proportions.of.rg <- numbers.of.red.gumball/n ps.k <- proportions.of.rg head(ps.k) mean.ps.k <- mean(ps.k) mean.ps.k hist(ps.k) #### set.seed(101) k <- 1000000 n <- 100 p <- 1/… text/html 2025-11-02T23:12:28+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/head_first_statistics/estimating_populations_and_samples/mean_of_proportions_output?rev=1762125148&do=diff > set.seed(101) > k <- 1000 > n <- 100 > p <- 1/4 > q <- 1-p > # in order to clarify what we are doing > # X~B(n,p) 일 때, 100개의 검볼을 샘플링해서 > # red gumball을 세봤더니 > rbinom(1,n,p) # 24개 였다라는 뜻 [1] 24 > > # 아래는 이것을 1000번 (k번) 한 것 > numbers.of.red.gumball <- rbinom(k, n, p) > head(numbers.of.red.gumball) [1] 18 27 27 22 23 26 > > # 아래처럼 n으로 (100개의 검볼이 총 숫자이므로) > # 나눠주면 비율을 구할 수 있다 > proportions.of.rg <- numbers.of.red.gumball/n > ps.k <- proportions.of.rg > head(ps.k) [1] 0.18 0.27 0.27 0.22 0.23 … text/html 2025-11-04T23:01:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/head_first_statistics/estimating_populations_and_samples/sampling_distribution_of_means_in_r?rev=1762297265&do=diff ###### # sampling distribution of means ###### ss <- 30 # 30 bags of gums m <- 10 # average # of gums in a bag va <- 1 # sd <- sqrt(va) # variance s.30 <- rnorm(ss, m, sd) s.30 # no natural numbers nm.s.30 <- round(s.30,0) # natural numbers sk <- nm.s.30 sk m.sk <- mean(sk) m.sk v.sk <- var(sk) v.sk sd.sk <- sd(sk) sd.sk ss <- 100 # size, from 30 to 100 set.seed(101) iter <- 10000 # means <- c() means <- rep(NA, iter) for (i in 1:iter) { m.bags <- rnorm(ss,m,sd) nm.bags <- round(m.bag… text/html 2025-11-04T23:00:39+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/head_first_statistics/estimating_populations_and_samples/sampling_distribution_of_means_in_r_output?rev=1762297239&do=diff > ###### > # sampling distribution of means > ###### > > ss <- 30 # 30 bags of gums > m <- 10 # average # of gums in a bag > va <- 1 # > sd <- sqrt(va) # variance > > s.30 <- rnorm(ss, m, sd) > s.30 # no natural numbers [1] 10.227850 7.698154 9.373175 8.417650 8.048828 9.132477 [7] 10.748230 10.441819 8.235895 9.230239 9.990201 7.530567 [13] 10.285544 11.202872 7.940989 10.076604 8.784941 7.859567 [19] 9.521232 8.795141 10.998430 9.794178 10.739007 10.648204 [25] 10.251162…