[英]How to draw confidence bounds to better demonstrate the confidence interval on ggplot2?
[英]Draw confidence interval on histogram with ggplot2
下面的代碼繪制了平均值的采樣分布,並計算了20個95%置信區間。 如何在直方圖上繪制置信區間,如下面的Photoshopped圖像所示?
# 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())
您可能要構建一個包含間隔的data.frame,然后添加一層水平誤差線以繪制它們。 首先,我將范圍轉換為data.frame
xx<-llply(1:20, function(x) my_confidence_intervals())
xx<-data.frame(y=1:20*50, x=do.call(rbind, xx))
現在我將它們添加到情節中
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)
這使
請注意,在創建data.frame時,我為每個范圍明確設置了y值。
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