A null-hypothesis is a formal proposition in statistical testing that posits no effect, no difference, or no relationship between measured variables. It serves as the default assumption that any observed pattern in data arises from random variation rather than a genuine effect. Parameters: (1) the specific variables under investigation, (2) the direction of the alternative (one-tailed or two-tailed), (3) the effect size considered meaningful. It persists through the institutional practice of hypothesis testing in scientific research, where it is systematically challenged by empirical data and peer review. [formal: hypothesis_null | substrate: mind | horizon: a moment | explicit: yes | epoch: 0.01]
Accepted ontology entry
null-hypothesis
A null-hypothesis is a formal proposition in statistical testing that posits no effect, no difference, or no relationship between measured variables. It serves as the default assumption that any observed pattern in data arises from random…
Definition
Why it is in scope
A human-made proposition in statistical testing that asserts no effect, no difference, or no relationship exists between variables. It is the default assumption against which empirical evidence is weighed, built to persist through the practice of scientific hypothesis testing and peer review.
Names and aliases
- null-hypothesisen · CANONICAL
Relations from this entry
- cmrcnskut00ww13vzhdk6xjwnINSTANCE_OF →
null-hypothesis is a specific kind of hypothesis — the one positing no effect/no difference, set up to be tested and potentially rejected. A competent speaker would call a null hypothesis 'a hypothesis.' Nearest kind: hypothesis.
Relations to this entry
- cmrwavehv00jskyo6t73uv4rk← DEPENDS_ON
multiple-comparisons operates by inflating the Type I error rate of null-hypothesis testing: when you conduct multiple null-hypothesis tests simultaneously, the probability that at least one null hypothesis is incorrectly rejected increases. The removal test: remove null-hypothesis and multiple-comparisons has nothing to operate on — its entire mechanism is the interaction of multiple null tests. The practice of multiple-comparisons correction exists solely because of null-hypothesis testing.
- cmrwbs6pa00lwkyo66ry5sxjf← DEPENDS_ON
Significance-testing requires null-hypothesis to operate: the entire practice evaluates whether data contradict a null hypothesis. Remove null-hypothesis and significance-testing has no target to test — the p-value computation, rejection regions, and decision rules all presuppose a null hypothesis. The removal test passes.
- cmrwa9lop00iekyo6t6jw7bql← DEPENDS_ON
Hypothesis-testing requires null-hypothesis to operate: the practice of testing hypotheses against a null is constitutive of hypothesis-testing as a statistical concept. Remove null-hypothesis and hypothesis-testing has no defined operation — there is no 'test' without a null to test against.
- cmrw9hpjd00fnkyo62okra5lp← DEPENDS_ON
The p-value is defined as the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. Remove null-hypothesis and the p-value has no definition — it cannot be calculated or even stated without the null hypothesis concept.
- cmrwc3ng900mtkyo6gq7p9xgn← DEPENDS_ON
Direction tested: null-hypothesis predates type-ii-error. Removal test: remove null-hypothesis and type-ii-error ceases to operate — type-II error is defined as failing to reject a false null hypothesis. Without the null concept, the error has no meaning. Valid DEPENDS_ON.
Record identity
- Created
- Jul 22, 2026, 4:09 PM UTC
- Content hash
- b0b28a27779ad3bac5baa530bb0ddf4352733663810dcbfd9b9d95b002d8939f