Reputation: 3208
Given a table of values (say between 0 to 100) and the attached plot, what would be the simplest way using R to calculate how many of the data points fall between values 20 - 60 (the red box in the image)?
And is there a way to create that red box using R's plotting functions (I did it using a image editor...)?
Thanks for the help.
Upvotes: 4
Views: 9675
Reputation: 162371
To calculate the probability mass contained within the interval:
x <- rnorm(1e6) ## data forming your empirical distribution
ll <- -1.96 ## lower bound of interval of interest
ul <- 1.96 ## upper bound of interval of interest
sum(x > ll & x < ul)/length(x)
# [1] 0.949735
And then to plot the histogram and the red box:
h <- hist(x, breaks=100, plot=FALSE) # Calculate but don't plot histogram
maxct <- max(h$counts) # Extract height of the tallest bar
## Or, if you want the height of the tallest bar within the interval
# start <- findInterval(ll, h$breaks)
# end <- findInterval(ul, h$breaks)
# maxct <- max(h$counts[start:end])
plot(h, ylim=c(0, 1.05*maxct), col="blue") # Plot, leaving a bit of space up top
rect(xleft = ll, ybottom = -0.02*maxct, # Add box extending a bit above
xright = ul, ytop = 1.02*maxct, # and a bit below the bars
border = "red", lwd = 2)
Upvotes: 13
Reputation: 132736
set.seed(42)
x <- rlnorm(5000) #some data
hist(x) #histogram
rect(7,-50,10,100,border="red") #red rectangle
table(cut(x,breaks=c(0,7,10,Inf)))/length(x) #fraction of values in intervals
#(0,7] (7,10] (10,Inf]
#0.9754 0.0136 0.0110
Cut
categorizes the values according to which interval they belong in. table
then creates a table of counts, which then can be divided by the total count length(x)
.
Upvotes: 8