Testing For Differences
In scientific and medical research, null hypotheses play a major role in testing the significance of differences in treatment and control groups. This use, while widespread, offers several grounds for criticism, including straw man, Bayesian criticism and publication bias.
The typical null hypothesis at the outset of the experiment is that no difference exists between the control and experimental groups (for the variable being compared). Other possibilities include:
- that values in samples from a given population can be modeled using a certain family of statistical distributions.
- that the variability of data in different groups is the same, although they may be centered around different values.
Read more about this topic: Null Hypothesis
Famous quotes containing the words testing and/or differences:
“Is this testing whether I’m a replicant or a lesbian, Mr. Deckard?”
—David Webb Peoples, U.S. screenwriter, and Ridley Scott. Rachel, Blade Runner, being tested to determine if she is human or machine (1982)
“What strikes many twin researchers now is not how much identical twins are alike, but rather how different they are, given the same genetic makeup....Multiples don’t walk around in lockstep, talking in unison, thinking identical thoughts. The bond for normal twins, whether they are identical or fraternal, is based on how they, as individuals who are keenly aware of the differences between them, learn to relate to one another.”
—Pamela Patrick Novotny (20th century)