2019 Biostat Class 5 Regression by Alan Grafen & Rosie Hails

2019 Biostat Class 5 Regression by Alan Grafen & Rosie Hails

## ─ Attaching packages ───────────────────────────────────── tidyverse 1.3.0 ─

## ✔ ggplot2 3.2.1     ✔ purrr   0.3.3
## ✔ tibble  2.1.3     ✔ dplyr   0.8.3
## ✔ tidyr   1.0.0     ✔ stringr 1.4.0
## ✔ readr   1.3.1     ✔ forcats 0.4.0

## ─ Conflicts ─────────────────────────────────────── tidyverse_conflicts() ─
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

#   read.csvではなくread_csvを使用，read_csvでも可能
Main_Data <- read_csv("/Users/gakugaku/Dropbox/#_2 授業/2019生物統計学/2019Biostat_Class_1/Data/BioStat4fat.csv")
names(Main_Data) <- c("体重","脂肪")
datatable(Main_Data)

g1 <- ggplot(Main_Data, 
             aes(x=体重,y=脂肪))+
   theme(text=element_text(family="HiraKakuPro-W3",size=10))
g2 <- g1 +geom_point()
g2

g1 <- ggplot(Main_Data, 
             aes(x=体重,y=脂肪))+
   theme(text=element_text(family="HiraKakuPro-W3",size=10))
g2 <- g1 +geom_point()
g3 <- g2+ geom_hline(yintercept=mean(Main_Data$脂肪))
g3