Code from this tweet: https://twitter.com/drob/status/840636042470400000

sample-size-power.R

library(tidyverse)
library(broom)
library(scales)
theme_set(theme_minimal())

crossing(n = round(10 ^ seq(1, 7, .1)),
         delta = 10 ^ seq(-1, -3, -1),
         sig.level = .05,
         sd = .3) %>%
  invoke(power.t.test, ., type = "one.sample") %>%
  tidy() %>%
  ggplot(aes(n, power, color = percent(delta))) +
  geom_line() +
  geom_hline(lty = 2, yintercept = .9) +
  scale_x_log10(labels = comma_format()) +
  scale_y_continuous(labels = percent_format()) +
  labs(x = "Number of observations (log scale)",
       y = "Power of one-sample t-test",
       color = "Effect size",
       title = "Power of one-sample t-test depending on sample size",
       subtitle = "Standard deviation = .3; dashed line shows power = 90%")