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The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H 1 , H 2 , ..., H m . Using a statistical test , we reject the null hypothesis if the test is declared significant.
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If they overlap at right angles, the greatest extent of the overlap is much smaller than if they overlap in near parallel. Thus a low DOP value represents a better positional precision due to the wider angular separation between the satellites used to calculate a unit's position.
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For a Type I error, it is shown as α (alpha) and is known as the size of the test and is 1 minus the specificity of the test. This quantity is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test.
In order for the final HEP calculation to be valid, the following assumptions are required to be fulfilled: There exists a seismic event initiator that leads to the establishment of air-based ventilation on the ITP processing tanks 48 and 49, possibly 50 in some cases.
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As for Q-convergence, sequences with larger orders converge more quickly and those with smaller rates converge more quickly for a given order, so these greatest-rate-lower-bound error-upper-bound sequences are those that have the greatest possible and the smallest possible given that .