R in a Nutshell

t-Test Design

If you are designing an experiment where you will use a t-test to check the significance of the results (typically, an experiment where you calculate the mean value of a random variable for a “test” population and a “control” population), then you can use the power.t.test function to help design the experiment:

power.t.test(n = NULL, delta = NULL, sd = 1, sig.level = 0.05,
             power = NULL,
             type = c("two.sample", "one.sample", "paired"),
             alternative = c("two.sided", "one.sided"),
             strict = FALSE)

For this function, n specifies the number of observations (per group); delta is the true difference in means between the groups; sd is the true standard deviation of the underlying distribution; sig.level is the significance level (Type I error probability); power is the power of the test (1 − Type II error probability); type specifies whether the test is one sample, two sample, or paired; alternative specifies whether the test is one or two sided; and strict specifies whether to use a strict interpretation in the two-sided case. This function will calculate either n, delta, sig.level, sd, or power, depending on the input. You must specify at least four of these parameters: n, delta, sd, sig.level, power. The remaining argument must be null; this is the value that the function calculates.