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.
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