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--- b:head_first_statistics:measuring_central_tendency [2024/09/08 23:30] – [e.g. 2] hkimscil
+++ b:head_first_statistics:measuring_central_tendency [2026/09/08 23:24] (current) – [outlier] hkimscil
@@ Line 31: / Line 31: @@
 \begin{equation*}
 \begin{split}
-\mu = \frac{\sum\limits_{}^{} \text{fx}}{\sum{\text{f}}}
+\mu = \frac{\sum\limits_{}^{} \text{fx}}{\sum{\text{f.nothing}}}
     = \frac{1 \text{x} 19 + 3 \text{x} 20 + 1 \text{x} 21}{5}
 \end{split}
 \end{equation*}
+<code>
+> # mean
+> x <- c(19, 19, 20, 20, 20, 21)
+> sum(x)
+[1] 119
+> length(x)
+[1] 6
+> sx <- sum(x)
+> nx <- length(x)
+> sx/nx
+[1] 19.83333
+> mean(x)
+[1] 19.83333
+</code>
 ===== outlier =====
@@ Line 40: / Line 56: @@
 [{{eg.distribution.jpg}}]
 </WRAP>
+<code>
+> # mean
+> x <- c(19, 19, 20, 20, 20, 21)
+> sx <- sum(x)
+> nx <- length(x)
+> sx/nx
+[1] 19.83333
+> mean(x)
+[1] 19.83333
+>
+> y <- c(3,19,20,21,34,37)
+> mean(y)
+[1] 22.33333
+>
+> xy <- cbind(x, y)
+> boxplot(xy, col=c("orange", "purple"),
++         names = c("x", "y"))
+</code>
+{{.:pasted:20260908-232337.png}}
 ===== skewedness =====
+see [[:b/head_first_statistics/visualization#histogram_skewedness]]
 <WRAP info>
 skewedness: 왜도
@@ Line 104: / Line 140: @@
 ==== e.g. 1 ====
 quartile 명령어는 r에서는 없다. 대신 quantile을 사용한다. 둘은 비슷하나 quantile은 4분위 이상의 것을 한다.
+교재에서 구하는 quartile방식은 알아두되, 실제에서는 R에서 quantile을 사용하여 quartile을 구하도록 한다. see [[:quartile]]
 R에서
@@ Line 267: / Line 303: @@
 <code>
 ## answer
+n <- 3+2+2 +3+4+4
+n
+mean.duckc <- 17
+median.duckc <- 17
+tot <- mean.duckc * n
+# 2 :: 4 인것은 이미 알고 있음
+known.sum <- (1*3)+(2*4)+(3*2)+(31*2)
+tot - known.sum
+# 227 = (32*4) + (33*3) 이므로
 duckc <- c(1,1,1,2,2,2,2,3,3,31,31,32,32,32,32,33,33,33)
 mean(duckc)