For a continuous variable it is 0.5 but for a discrete variable the answer depends on the probability of the variable taking the mean value. It is half of the rest of the probability.
If the discrete variable X has mean m and Prob(X = m) is p
then Prob(X > m) = (1 - p)/2.
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It means that there is a probability of 0.0968 that an observation as extreme as this occurred purely by chance.
The probability is 0.4448, approx.
It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.
From a probability perspective fair means equal probability.
A negative deviation means that the observation is smaller than whatever it is that the deviation is being measured from.