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The selected descriptors were then used to perform an MLR study until a valid model including: the critical probability P value < 0.05 for all descriptors and for the complete model, The Fisher static, the coefficient of determination, the mean squared error and the multi-collinearity test, internal and external validations, in addition to the Y-Randomization.
Then, those three chosen descriptors were used as input to perform an MLR study on each activity until a valid model including: the critical probability p value <0.05 for all descriptors and for the complete model, the Fisher criterion, the determination coefficient, the mean squared error, the multi-colinearity test, and the internal, external validations, in addition to the Y-randomization.
If the distance between the lattice points decreases to zero in what is called the scaling limit, the critical probability approaches a final value.
At a value smaller than critical probability the number of communities are identified for the given data as probable number of knowledge rules.
In 1992 British physicist John Cardy postulated a formula for the final value of the critical probability.
Probability values are typically expressed in decimals or fractions-with a probability value close to "one" indicating that an event is highly probable, while a probability value close to "zero" indicates that an event that is highly improbable.
How does that compare with your probability value as calculated?
A probability value of <.05 was significant.
Probability value.
p-value Probability value.
P values were calculated with one tailed probability value.
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CEO of Professional Science Editing for Scientists @ prosciediting.com