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End plate potentials (EPPs) are the voltages which cause depolarization of skeletal muscle fibers caused by neurotransmitters binding to the postsynaptic membrane in the neuromuscular junction. They are called "end plates" because the postsynaptic terminals of muscle fibers have a large, saucer-like appearance.
The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1]
In the older notion of nonparametric skew, defined as () /, where is the mean, is the median, and is the standard deviation, the skewness is defined in terms of this relationship: positive/right nonparametric skew means the mean is greater than (to the right of) the median, while negative/left nonparametric skew means the mean is less than (to ...
where is the beta function, is the location parameter, > is the scale parameter, < < is the skewness parameter, and > and > are the parameters that control the kurtosis. and are not parameters, but functions of the other parameters that are used here to scale or shift the distribution appropriately to match the various parameterizations of this distribution.
The aggregate sum of many MEPPs is an end plate potential (EPP). A normal end plate potential usually causes the postsynaptic neuron to reach its threshold of excitation and elicit an action potential. [1] Electrical synapses do not use quantal neurotransmitter release and instead use gap junctions between neurons to send current flows between ...
The exponentially modified normal distribution is another 3-parameter distribution that is a generalization of the normal distribution to skewed cases. The skew normal still has a normal-like tail in the direction of the skew, with a shorter tail in the other direction; that is, its density is asymptotically proportional to for some positive .
A Pearson density p is defined to be any valid solution to the differential equation (cf. Pearson 1895, p. 381) ′ () + + + + = ()with: =, = = +, =. According to Ord, [3] Pearson devised the underlying form of Equation (1) on the basis of, firstly, the formula for the derivative of the logarithm of the density function of the normal distribution (which gives a linear function) and, secondly ...
The most useful of these are , called the L-skewness, and , the L-kurtosis. L-moment ratios lie within the interval (−1, 1) . Tighter bounds can be found for some specific L-moment ratios; in particular, the L-kurtosis τ 4 {\displaystyle \tau _{4}} lies in [−1 /4, 1) , and [ 1 ] 1 4 ( 5 τ 3 2 − 1 ) ≤ τ 4 < 1 . {\displaystyle {\tfrac ...