r:general_statistics
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| r:general_statistics [2017/11/06 07:58] – [e.g.,] hkimscil | r:general_statistics [2019/10/11 07:56] (current) – [Forming a Confidence Interval for a Mean] hkimscil | ||
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| Line 497: | Line 497: | ||
| ====== Forming a Confidence Interval for a Mean ====== | ====== Forming a Confidence Interval for a Mean ====== | ||
| - | < | + | < |
| + | > set.seed(1024) | ||
| + | > x <- rnorm(50, mean=100, sd=15) | ||
| + | > s <- sd(x) | ||
| > m <- mean(x) | > m <- mean(x) | ||
| > n <- length(x) | > n <- length(x) | ||
| Line 509: | Line 512: | ||
| > SE | > SE | ||
| [1] 2.458358 | [1] 2.458358 | ||
| - | > E <- qt(.975, df=n-1)*SE | + | ## qt fun: qt(prob, df) zscore 2점에 해당하는 점수는? |
| + | > qtv <- qt(.975, df=n-1) | ||
| + | > qtv | ||
| + | [1] | ||
| + | ## qtv는 2에 해당하는 95퍼센트 CL | ||
| + | ## 이 때의 CI는 | ||
| + | > E <- qtv*SE | ||
| > E | > E | ||
| [1] 4.940254 | [1] 4.940254 | ||
| Line 517: | Line 526: | ||
| </ | </ | ||
| - | < | + | < |
| + | > t.test(x, mu=98) | ||
| One Sample t-test | One Sample t-test | ||
| data: x | data: x | ||
| - | t = 39.052, df = 49, p-value | + | t = 0.37089, df = 49, p-value |
| - | alternative hypothesis: true mean is not equal to 0 | + | alternative hypothesis: true mean is not equal to 98 |
| 95 percent confidence interval: | 95 percent confidence interval: | ||
| - | | + | |
| sample estimates: | sample estimates: | ||
| mean of x | mean of x | ||
| - | 96.00386 | + | 98.83223 |
| + | |||
| + | > t.test(x, mu=100) | ||
| + | |||
| + | One Sample t-test | ||
| + | |||
| + | data: x | ||
| + | t = -0.52043, df = 49, p-value = 0.6051 | ||
| + | alternative hypothesis: true mean is not equal to 100 | ||
| + | 95 percent confidence interval: | ||
| + | 94.32303 103.34143 | ||
| + | sample estimates: | ||
| + | mean of x | ||
| + | | ||
| + | |||
| + | > t.test(x, mu=95) | ||
| + | |||
| + | One Sample t-test | ||
| + | |||
| + | data: x | ||
| + | t = 1.7079, df = 49, p-value = 0.09399 | ||
| + | alternative hypothesis: true mean is not equal to 95 | ||
| + | 95 percent confidence interval: | ||
| + | 94.32303 103.34143 | ||
| + | sample estimates: | ||
| + | mean of x | ||
| + | | ||
| + | |||
| + | > | ||
| </ | </ | ||
| Line 793: | Line 831: | ||
| < | < | ||
| > t.test(sleep.wide$group1, | > t.test(sleep.wide$group1, | ||
| + | |||
| + | Paired t-test | ||
| + | |||
| + | data: sleep_wide$group1 and sleep_wide$group2 | ||
| + | t = -4.0621, df = 9, p-value = 0.002833 | ||
| + | alternative hypothesis: true difference in means is not equal to 0 | ||
| + | 95 percent confidence interval: | ||
| + | | ||
| + | sample estimates: | ||
| + | mean of the differences | ||
| + | -1.58 | ||
| + | |||
| </ | </ | ||
| The paired t-test is equivalent to testing whether difference between each pair of observations has a population mean of 0. (See below for comparing a single group to a population mean.) | The paired t-test is equivalent to testing whether difference between each pair of observations has a population mean of 0. (See below for comparing a single group to a population mean.) | ||
| - | < | + | < |
| - | > Error in t.test(sleep.wide$group1 - sleep.wide$group2, | + | |
| + | One Sample | ||
| + | |||
| + | data: sleep_wide$group1 - sleep_wide$group2 | ||
| + | t = -4.0621, df = 9, p-value = 0.002833 | ||
| + | alternative hypothesis: true mean is not equal to 0 | ||
| + | 95 percent confidence interval: | ||
| + | -2.4598858 -0.7001142 | ||
| + | sample estimates: | ||
| + | mean of x | ||
| + | -1.58 | ||
| </ | </ | ||
r/general_statistics.1509924499.txt.gz · Last modified: 2017/11/06 07:58 by hkimscil