# significance test

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Related to significance test: significance level, T test

## significance test

(STATISTICS) a test designed to assess whether an observed (numerical) result can have occurred by chance. The result of the test is expressed as a statistic (e.g. t-ratio, F-ratio) which can be assessed against different levels of probability. It is usual to accept a level of probability of 0.05, i.e. that there is only a 5% probability of the result having occurred by chance.

Examples of significance tests are the t-test (parametric) and the Wilcoxon (non- parametric) (see STATISTICS AND STATISTICAL ANALYSIS). These tests are designed to test for the significance of the observed difference between two groups of data. For example, in social survey work two samples may be taken, racial attitudes in cities with and without ethnic minority problems, perhaps. There may be an apparent difference (numerical) between these groups, but the groups were samples and therefore the data is subject to SAMPLING ERROR. The difference between them must therefore be tested to see if there is a statistically significant difference between them. Significance tests are designed to set up a NULL HYPOTHESIS, stating ‘no difference’, and the test result either confirms or disconfirms this.

References in periodicals archive ?
In East China, though the correlation between the simulated and observed latent heat flux passed the significance test with the significance level of 0.01, its value is only 0.36.
Number of Bands Passed the 0.05 Significance Test. From Figures 6 and 7, it could be seen that as the order increases, so did the number of bands from areas A and B that passed the 0.05 significance test.
Causes of pattern outliers of homes, by type of model Types of models Number of houses that did not satisfy the requirements (a) Shape test (b) Significance test (c) [R.sup.2] test 5-P CP 2 8 8 4-P CP 0 9 8 3-P CP cooling 0 11 6 3-P CP heating 1 4 4 2-P CP 0 9 12 Types of models Number of houses that did not satisfy the requirements (d) Data population test 5-P CP 0 4-P CP 0 3-P CP cooling 1 3-P CP heating 0 2-P CP 0 Table 4.
Significance tests Die Hard: The amazing persistence of a probabilistic misconception.
Applying the significance test of the mean differences for the pair samples, we get a t-value of 5.72 (df-15), p <0.05, which supports the acknowledgment that the repetition was significantly improved.
The methodological contribution of current study is given in three stages: Incorporation of Pearson's chi-square and Yates's correction to the re-scaled data; Construction of the significance test for kurtosis coefficient associated with the first principal component and Evaluation of the Monte Carlo simulation test.
If these answers are satisfactory, then the risk manager can feel more comfortable with the significance test.
* Preparing the prediction--once we have chosen a regression equation whose correlation coefficient value is big enough and which is adequate from the perspective of the significance test, the decision-making party (the manager) can use this equation as a basis for analysis for the prediction that he intends to make.
In EU nature conservation law, when applying the habitats assessment of the European Habitats Directive (article 6) during the significance test and the appropriate assessment, only a few strictly limited ES could be taken into consideration, thus excluding entire categories of other ES.
To ensure an even smaller chance of having a Type I error, the statistical significance test can be set at 0.01.
Each measured fingerprint is fully analyzed: some of the fingerprints can be clustered and integrated under the statistical significance test. Then, the finally validated fingerprint by the significance test has its statistical significance among the other fingerprints in a reference DB.
When the authors assessed the effect of depression on the types of dieting behaviors, they determined that, among women, depression was negatively related to healthy dieting behaviors (significance test of the simple slope t (192) = -2.59) and positively related to unhealthy dieting behaviors (t[192]= 3.61), with P less than .01 for both.

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