以下代码绘制平均值的采样分布图并计算20批95%置信区间。如何在直方图上绘制置信区间,如下面的Photoshop图像?
# plot sampling distribution of mean -----------------------------------------------------------
set.seed(1)
population <- rnorm(10000, 3, 3)
population_mean <- mean(population)
my_sample <- sample(population, 100, replace = FALSE)
standard_error <- sqrt(var(my_sample)/length(my_sample))
sampling_distribution_of_mean <- rnorm(10000, mean = population_mean, sd = standard_error)
library(ggplot2)
ggplot(data.frame(x = sampling_distribution_of_mean), aes(x)) + geom_histogram() + geom_vline(xintercept = population_mean, color = "red")
# calculate 20 lots of 95% confidence intervals -----------------------------------------------------------
my_confidence_intervals <- function(){
my_sample <- sample(population, 100, replace = FALSE)
sample_mean <- mean(my_sample)
standard_error <- sqrt(var(my_sample)/length(my_sample))
margin_of_error <- 1.96*standard_error
mean_minus_margin_of_error <- sample_mean - margin_of_error
mean_plus_margin_of_error <- sample_mean + margin_of_error
c(mean_minus_margin_of_error, mean_plus_margin_of_error)
}
library(plyr)
llply(1:20, function(x) my_confidence_intervals())
答案 0 :(得分:8)
您可能希望构建一个包含间隔的data.frame,然后添加一层水平误差线来绘制它们。首先,我将您的范围转换为data.frame
xx<-llply(1:20, function(x) my_confidence_intervals())
xx<-data.frame(y=1:20*50, x=do.call(rbind, xx))
现在我将它们添加到情节
ggplot(data.frame(x = sampling_distribution_of_mean), aes(x)) +
geom_histogram() +
geom_vline(xintercept = population_mean, color = "red") +
geom_errorbarh(aes(y=y, x=x.1, xmin=x.1, xmax=x.2), data=xx, col="#0094EA", size=1.2)
给出了
请注意,我在创建data.frame时为每个范围显式设置了y值。