Performing t-tests and plotting density of page load times

stat_test.R

library(ggplot2)
library(reshape)
library(plyr)

old_layout <- read.csv('log/old_layout.log', header=F, sep="\t")
old_layout <- old_layout$V1
new_layout <- read.csv('log/new_layout.log', header=F, sep="\t")
new_layout <- new_layout$V1

ds <- as.data.frame(cbind(old_layout[1:100], new_layout[1:100]))
colnames(ds) <- c('old_layout', 'new_layout')
ds.melt <- melt(ds)
cdat <- ddply(ds.melt, "variable", summarise, rating.mean=mean(value))

p <- ggplot(ds.melt, aes(x=value, fill=variable, color=variable)) +
  geom_density(alpha=.5) +
  ggtitle("Incidents dashboard page\nload time") +
  guides(fill = guide_legend(override.aes = list(colour = NULL))) +
  scale_fill_brewer(palette="Dark2", labels=c("Old layout", "New layout")) +
  scale_color_brewer(palette="Dark2",guide=FALSE) + 
  xlab("Load time, sec") + 
  theme_bw() + 
  theme(
    plot.title = element_text(vjust=1.5, size=20),
    axis.text.y = element_blank(),
    axis.text.y=element_blank(),
    axis.ticks.y=element_blank(),
    axis.title.y=element_blank(),
    legend.title=element_blank()
    )

print(p)

print(t.test(old_layout, new_layout, conf.level = 0.99))