null hypothesis

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Related to null hypotheses: Alternative hypothesis, P value

null hypothesis

[′nəl hī′päth·ə·səs]
(statistics)
The hypothesis that there is no validity to the specific claim that two variations (treatments) of the same thing can be distinguished by a specific procedure.

null hypothesis

a working hypothesis which states that there will be no statistically significant difference between the EXPERIMENTAL GROUP and CONTROL GROUP.

When an experiment is set up, or observational data collected, this is designed to test a HYPOTHESIS, or theory which has been developed from previous work. This is the EXPERIMENTAL HYPOTHESIS, and it states what the expected difference is between the groups if the theory is correct. The converse hypothesis is also conventionally stated: this is the null hypothesis, that predictions from the theory are incorrect, and there is no difference between the groups in the VARIABLE investigated. See also INDEPENDENT VARIABLE, DEPENDENT VARIABLE.

References in periodicals archive ?
0] hypothesis tests are statistically independent, then the probability distribution for the number of erroneously rejected null hypotheses will be binomial, yielding the probabilities for the possible numbers of erroneously rejected tests x,
Specifically, assumptions regarding the null hypotheses for the firms with minority win probabilities have a nontrivial impact on the analysis.
Besides, the appropriated notation for the null hypotheses 2 and 4 are
The following null hypotheses are tested in the context of a VECM to determine the causal relationship between stock prices and fiscal and monetary policies for Germany:
Null hypotheses of a unit root is rejected at 5% significance level or less.
The three null hypotheses were tested using chi-square analyses (Witte, 1989).
The null hypotheses of unit roots in the first differences of the married female labor force participation rate, the married female birth rate, and mean real female income are all rejected at the one-percent level.
Our results for the standard model are reported in Table 1, which presents the p-values, test statistics, and degrees of freedom for Wald tests for five null hypotheses of interest: (1) the coefficients on positive monetary shocks are jointly equal to zero; (2) the coefficients on positive monetary shocks sum to zero; (3) the coefficients on negative monetary shocks are jointly equal to zero; (4) the coefficients on negative monetary shocks sum to zero; and (5) the sum of the coefficients on positive and negative monetary shocks equal one another, that is, money supply shocks are symmetric in their effect on output.
Confidence of only 50% may be an anathema to those locked into testing null hypotheses, as, in their eyes, it is equivalent to testing against the null hypothesis at a P value of 0.
To explore the purpose of this study in a systematic way, the following null hypotheses were tested:
Thus, statistical null hypotheses may differ across the levels of hierarchical structure, depending on a proper specification of the fixed and random effects.
One advantage of the likelihood ratio or conditional probability is that they can be easily modified to accommodate different null hypotheses.