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The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.
When the two modes are unequal the larger mode is known as the major mode and the other as the minor mode. The least frequent value between the modes is known as the antimode. The difference between the major and minor modes is known as the amplitude. In time series the major mode is called the acrophase and the antimode the batiphase ...
The term "mode" in this context refers to any peak of the distribution, not just to the strict definition of mode which is usual in statistics. If there is a single mode, the distribution function is called "unimodal". If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2]
Kress defines 'mode' in two ways. One: a mode is something that can be socially or culturally shaped to give something meaning. Images, pieces of writing, and speech patterns are all examples of modes. [6] Two: modes are semiotic, shaped by intrinsic characteristics and their potential within their medium, as well as what is required of them by ...
The form of a modus ponens argument is a mixed hypothetical syllogism, with two premises and a conclusion: If P, then Q. P. Therefore, Q. The first premise is a conditional ("if–then") claim, namely that P implies Q. The second premise is an assertion that P, the antecedent of the conditional claim, is the case.
Related to the diatonic modes are the eight church modes or Gregorian modes, in which authentic and plagal forms of scales are distinguished by ambitus and tenor or reciting tone. Although both diatonic and Gregorian modes borrow terminology from ancient Greece , the Greek tonoi do not otherwise resemble their medieval/modern counterparts.
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When =, =, we can easily see the separatrix and the two basins of attraction by solving for the trajectories backwards in time. In the FitzHugh–Nagumo model, when the linear nullcline pierces the cubic nullcline at the left, middle, and right branch once each, the system has a separatrix. Trajectories to the left of the separatrix converge to ...