| Parameter |
A parameter is a fixed, but unknown population value. Sample
statistics are used to estimate parameters. |
| Standard error (SE) |
Measure for the standard deviation of a parameter estimator. In case
of a sample mean, it is equal to the estimated standard deviation
divided by the square root of the underlying sample size. |
| Confidence interval (CI) |
An estimate for plausible population parameters. Several different
CIs can be constructed for the comparison of
two means, depending on the employed design and the desired
interpretation. Still, each CI can be broken down
to the simple formula: "Mean ± Standard Error ✕
Coefficient" (CI = M ±
SE ✕ tdf;1-1-α/2
|
| Confidence interval for an individual mean
(CIM) |
This CI is constructed from the standard error of
the mean (SEM) and can be used to
compare this mean to any fixed parameter. It corresponds to a
one-sample t-test and does not yield any precise
information about the difference between two sample means. |
| Confidence interval for the difference between two means from
independent samples (CID) |
This CI is constructed from the between-subjects
standard error of the difference between two means
(SED). It thus corresponds to a
t-test for independent samples and can be used
for inferences about the difference between both means. |
| Confidence interval for the paired difference between two means
(CIPD) |
This CI is constructed from the standard error of
the difference between two dependent sample means (paired
differences). It is thus applicable for within-subjects designs and
equivalent to a paired-samples t-test. |
