Between-subjects statistics for one group are used to test hypotheses about the dispersal of distributions. The choice of between-subjects statistical test for one group depends upon the scale of measurement of the outcome.
For categorical outcomes and one group, researchers make a null hypothesis about the dispersal of an outcome and test the observed dispersal against the null dispersal.
With ordinal outcomes, researchers make an a priori hypothesis as to what the median value will be in a distribution and tests the observed median against the hypothesized median.
Finally, a hypothesized mean for a given population can be hypothesized and tested against the observed mean in a sample to see if there is a statistically significant difference.
For categorical outcomes and one group, researchers make a null hypothesis about the dispersal of an outcome and test the observed dispersal against the null dispersal.
With ordinal outcomes, researchers make an a priori hypothesis as to what the median value will be in a distribution and tests the observed median against the hypothesized median.
Finally, a hypothesized mean for a given population can be hypothesized and tested against the observed mean in a sample to see if there is a statistically significant difference.
The outcome represents numerical designations or categorical values that describe exposures, characteristics, phenomena, events, or group membership.
The outcome variable is measured using an ordered numerical continuum, such as a Likert scale.
The outcome variable is an actual number that provides both a measure of distance and magnitude due to having a "true zero."
