### 요약 _No response_ ### 카테고리 _No response_ ### 파일 슬러그 log-52 ### 저장 폴더 _No response_ ### 태그 study ### 작성일 _No response_ ### 수정일 _No response_ ### 본문 ## TIL - Study - Today, I reviewed Part 2 of the "Introduction to Statistics". - I realized that passively viewing the lecture on a mobile phone without a keyboard was inefficient for my learning. - Swiching to a PC environment significantly enhanced my comprehension and allowed for practice. - Additionally, I supplemented the lecture by reviewing the corresponding textbook chapters. - The R script provided below illustrates the statistical computing exercises covered in Part 2. ### R Code ```r library(ggplot2) transp = c("bicycle", "bus", "bus", "walking", "bus", "bicycle", "bicycle", "bus") dat1 = data.frame(transp) library(forcats) ggplot(data=dat1) + geom_bar(mapping=aes(x=fct_infreq(transp))) + xlab("Transportation") obesity = factor(c("underweight", "normal", "overweight", "obese"), levels=c("underweight", "normal", "overweight", "obese")) count = c(6, 69, 27, 13) perc = count / sum(count) * 100 dat2 = data.frame(obesity, count, perc) ggplot(data=dat2) + geom_bar(mapping=aes(x=obesity, y=perc), stat="identity") + xlab("Obesity") + ylab("Percentage(%)") table(transp) dat3 = data.frame(transportation=c("bus", "bicycle", "walking"), count=c(15, 13, 4)) ```
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github-actions commentedon Feb 28, 2026
포스트가 자동 반영되었습니다:
_posts/diary/til/2026-02-28-log-52.mdchore(post): publish issue #17
chore(post): publish issue #17
github-actions commentedon Feb 28, 2026
포스트가 자동 반영되었습니다:
_posts/diary/til/2026-02-28-log-52.md