R語言用ggstatsplot包做方差分析和繪圖
R語言ggstatsplot包做卡方檢驗(yàn)
library(ggstatsplot)
library(dplyr)
mtcars_new <- mtcars %>%
tibble::rownames_to_column(., var = 'carname') #將mtcars的行名轉(zhuǎn)換成'carname列存儲(chǔ)叉袍，形成新的數(shù)據(jù)集
ggdotplotstats(mtcars_new, x = mpg, y = carname,
centrality.para = F, #不顯示集中趨勢統(tǒng)計(jì)量
results.subtitle = F, #不在圖中以副標(biāo)題的形式顯示統(tǒng)計(jì)結(jié)果
ggtheme = ggplot2::theme_classic(),#設(shè)置主題
messages = F
)
image.png
單樣本均值比較
1始锚、點(diǎn)圖
ggdotplotstats(mtcars_new, x = mpg, y = carname,
centrality.para = 'mean', #集中趨勢選擇均數(shù)(可選mean和median)
test.value = 15, #樣本均數(shù)與15進(jìn)行比較
test.value.line = T, #畫出比較值的垂直線
test.value.color = 'red', #比較值的標(biāo)簽顏色為red
test.value.size = 1.2#垂直線的寬度為1.2倍
)
Note: Shapiro-Wilk Normality Test for mpg : p-value = 0.123
image.png
2、頻數(shù)圖
gghistostats(mtcars_new, x = mpg,
binwidth = 3, #組距為3
normal.curve = T,
normal.curve.color = 'Orange',
centrality.para = 'mean',
test.value = 15,
test.value.line = T,
test.value.color = 'red',
bar.measure = 'mix' #既顯示頻數(shù)又顯示頻率
)
Note: Shapiro-Wilk Normality Test for mpg : p-value = 0.123
image.png
點(diǎn)圖與頻數(shù)圖若不設(shè)置“test.value”喳逛，則默認(rèn)與0進(jìn)行比較瞧捌。
兩樣本均值比較
str(sleep)
'data.frame': 20 obs. of 3 variables:
$ extra: num 0.7 -1.6 -0.2 -1.2 -0.1 3.4 3.7 0.8 0 2 ...
$ group: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
$ ID : Factor w/ 10 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
1、兩獨(dú)立樣本
ggbetweenstats(sleep, x = group, y = extra,
type = 'p', #參數(shù)(parameter)檢驗(yàn), np為非參數(shù)檢驗(yàn)
conf.level = 0.95,
mean.ci = T #圖中顯示均值的置信區(qū)間
)
Note: Shapiro-Wilk Normality Test for extra : p-value = 0.311
Note: Bartlett's test for homogeneity of variances for factor group: p-value = 0.743
image.png
2润文、兩配對(duì)樣本
ggwithinstats(sleep, x = group, y = extra,
type = 'p',
conf.level = 0.95,
mean.ci = T)
Note: Shapiro-Wilk Normality Test for extra : p-value = 0.311
Note: Bartlett's test for homogeneity of variances for factor group: p-value = 0.743
image.png
