Their high specificity (>95) make the probability of obtaining false positive results very low [ 11- 13].
The probability of obtaining the effect is thus dependent on the probability of obtaining the requisite number of hits on the appropriate target or targets.
This means that, before the measurement is made, the probability of obtaining the value a3 is unity and the probability of obtaining any other value of a is zero.
For example, it provides a formula for the probability of obtaining 10 sixes in 50 rolls of a die.
Hence, the probability of obtaining a number in the interval [x, y] equals (y − x)/(s − r).
In words, the expected value of X is the sum of each of the possible values of X multiplied by the probability of obtaining that value.
Second, before the measurement is made, the probability of obtaining the value a1 is c12, and that of obtaining the value a2 is c22, and so on.
The probability of obtaining better results correlates with its parameters.
Model 1 shows that the probability of obtaining a callback increases if the candidate is Italian.
The probability of being detected is equivalent to the probability of obtaining an erroneous model.
The probability of obtaining different samples can be deduced from the design and used for inference.
