问题描述
我正在查看性别之间的反应时间(计数数据)差异。但是我的假设确实有一些问题,因为我的自动绘图输出看起来很奇怪,而且我不太了解这是怎么回事。
[自动绘图] [1]
- 为什么我的Q-Q图看起来像楼梯?
- 为什么其他三个图看起来像这样(所有点在两个位置垂直对齐)?如果看起来像这样,我无法检查这些假设?
我的代码:
library(tidyverse)
library(ggplot2)
library(dplyr)
library(ggfortify)
library(tidyr)
rt <- read.csv(URL)
#rename
names(rt) <- c("Timestamp","ID","Gender","Pref_Reaction_time_1","Verbal_memory_score","Number_memory_score","Visual_memory_score","Weight_kgs","Handed","Nonpref_Reaction_time_ave","Pref_Reaction_time_2","Pref_Reaction_time_3","Pref_Reaction_time_4","Pref_Reaction_time_5","Pref_Reaction_time","Random_number")
#select only needed variables
rt <- dplyr::select(rt,ID,Gender,Verbal_memory_score,Number_memory_score,Visual_memory_score)
## Number Memory
#have a look at variable
ggplot(rt,aes(x=Number_memory_score)) +geom_histogram()
#filter out the weird data
rt2 <- filter(rt,Number_memory_score <25)
#check how it looks
ggplot(rt2,aes(x=Number_memory_score)) +geom_histogram(bins=10)
#does there seem to be a relationship btw the variables
ggplot (rt2,aes (x = Number_memory_score)) + geom_histogram () + facet_wrap (~Gender)
ggplot(rt2,aes(x=Gender,y=Number_memory_score))+ geom_point()+ geom_Boxplot() +ggtitle("Number")
#tiny difference
#create model
m_number <- glm(Number_memory_score ~ Gender,data=rt2,family=quasipoisson)
#check assumptions and output
autoplot(m_number) #looks weird
anova(m_number,test="F")
summary(m_number)
#very small part explained by gender
[1]: https://i.stack.imgur.com/5Kp2g.png
解决方法
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