My take on Pixar's situation, a statistical process control viewpoint as opposed to The Atlantic's linear regression.

Pixar.R

rm(list = ls())
library(qcc)

dat <- data.frame(name = c("Toy Story", "A Bug's Life", "Toy Story 2", 
			   "Monsters Inc", "Nemo", "Incredibles",
			   "Cars", "Ratatouille", "Wall-E", "Up", "Toy Story 3",
			   "Cars 2", "Brave", "Monsters U"),
       x = c(76, 77, 161, 185, 235, 224, 143, 213, 228, 273, 261, 79, 169, 137 ), 
       n = c(76, 84, 161, 193, 237, 231, 194, 222, 237, 278, 264, 203, 217, 175)
			 ) 

before.toy.story.3 <- dat[1:11,]                
after.toy.story.3  <- dat[12:14, ]

qcc(before.toy.story.3$x , sizes = before.toy.story.3$n, type = "p", 
    newdata = after.toy.story.3$x, newsizes = after.toy.story.3$n, 
    labels = before.toy.story.3$name, newlabels=after.toy.story.3$name,
    add.stats=FALSE, title = "Pixar's Fall?",
    ylab = "Rotten Tomatoes % Favorable", xlab = "Movie"
    )