sampling_distribution_in_r
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| sampling_distribution_in_r [2025/03/24 08:48] – hkimscil | sampling_distribution_in_r [2025/03/24 09:00] (current) – hkimscil | ||
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| ====== Sampling distribution in R e.g. 1 ====== | ====== Sampling distribution in R e.g. 1 ====== | ||
| < | < | ||
| + | # sampling distribution | ||
| n.ajstu <- 100000 | n.ajstu <- 100000 | ||
| mean.ajstu <- 100 | mean.ajstu <- 100 | ||
| Line 77: | Line 78: | ||
| ses[i] = sqrt(var(ajstu)/ | ses[i] = sqrt(var(ajstu)/ | ||
| } | } | ||
| + | ses.means4 <- sqrt(var(means4)) | ||
| + | ses.means25 <- sqrt(var(means25)) | ||
| + | ses.means100 <- sqrt(var(means100)) | ||
| + | ses.means400 <- sqrt(var(means400)) | ||
| + | ses.means900 <- sqrt(var(means900)) | ||
| + | ses.means1600 <- sqrt(var(means1600)) | ||
| + | ses.means2500 <- sqrt(var(means2500)) | ||
| + | ses.real <- c(ses.means4, | ||
| + | ses.means100, | ||
| + | ses.means900, | ||
| + | ses.means2500) | ||
| + | ses.real | ||
| ses | ses | ||
| Line 84: | Line 97: | ||
| lower.s2 <- mean(ajstu)-se.2 | lower.s2 <- mean(ajstu)-se.2 | ||
| upper.s2 <- mean(ajstu)+se.2 | upper.s2 <- mean(ajstu)+se.2 | ||
| - | data.frame(cbind(sss, | + | data.frame(cbind(sss, |
| </ | </ | ||
| + | 아웃풋 | ||
| < | < | ||
| - | > # sampling distribution | ||
| > n.ajstu <- 100000 | > n.ajstu <- 100000 | ||
| > mean.ajstu <- 100 | > mean.ajstu <- 100 | ||
| Line 170: | Line 182: | ||
| 6 1600 0.2500000 99.50000 100.5000 | 6 1600 0.2500000 99.50000 100.5000 | ||
| 7 2500 0.2000000 99.60000 100.4000 | 7 2500 0.2000000 99.60000 100.4000 | ||
| + | > sss <- c(4, | ||
| + | > ses <- rep (NA, length(sss)) # std errors | ||
| + | > for(i in 1: | ||
| + | + | ||
| + | + } | ||
| + | > ses.means4 <- sqrt(var(means4)) | ||
| + | > ses.means25 <- sqrt(var(means25)) | ||
| + | > ses.means100 <- sqrt(var(means100)) | ||
| + | > ses.means400 <- sqrt(var(means400)) | ||
| + | > ses.means900 <- sqrt(var(means900)) | ||
| + | > ses.means1600 <- sqrt(var(means1600)) | ||
| + | > ses.means2500 <- sqrt(var(means2500)) | ||
| + | > ses.real <- c(ses.means4, | ||
| + | + | ||
| + | + | ||
| + | + | ||
| + | > ses.real | ||
| + | [1] 4.9719142 2.0155741 0.9999527 0.5034433 0.3324414 0.2466634 | ||
| + | [7] 0.1965940 | ||
| + | > ses | ||
| + | [1] 5.0000000 2.0000000 1.0000000 0.5000000 0.3333333 0.2500000 | ||
| + | [7] 0.2000000 | ||
| + | > se.1 <- ses | ||
| + | > se.2 <- 2 * ses | ||
| + | > lower.s2 <- mean(ajstu)-se.2 | ||
| + | > upper.s2 <- mean(ajstu)+se.2 | ||
| + | > data.frame(cbind(sss, | ||
| + | | ||
| + | 1 4 5.0000000 4.9719142 90.00000 110.0000 | ||
| + | 2 25 2.0000000 2.0155741 96.00000 104.0000 | ||
| + | 3 100 1.0000000 0.9999527 98.00000 102.0000 | ||
| + | 4 400 0.5000000 0.5034433 99.00000 101.0000 | ||
| + | 5 900 0.3333333 0.3324414 99.33333 100.6667 | ||
| + | 6 1600 0.2500000 0.2466634 99.50000 100.5000 | ||
| + | 7 2500 0.2000000 0.1965940 99.60000 100.4000 | ||
| > | > | ||
| </ | </ | ||
| + | {{: | ||
| 문제 . . . . | 문제 . . . . | ||
| < | < | ||
| Line 189: | Line 237: | ||
| </ | </ | ||
| - | {{: | + | |
| ===== Sampling distribution in proportion in R ===== | ===== Sampling distribution in proportion in R ===== | ||
sampling_distribution_in_r.1742773735.txt.gz · Last modified: 2025/03/24 08:48 by hkimscil