The phrase "inferential power" is correct and usable in written English.
It can be used in contexts discussing reasoning, logic, or the ability to draw conclusions from evidence.
Example: "The study demonstrated the inferential power of the data collected, allowing researchers to make significant predictions about future trends."
Alternatives: "reasoning ability" or "deductive strength."
Computer simulations show that there are methods of theory application that vastly outstrip the inferential power of logical deduction.
Cautious Montony (resp. Cut) states that adding a consequence φ to the premise-set Γ does not lead to any decrease (resp. increase) in inferential power.
TAUT combined with MP gives us the full inferential power of the Propositional Calculus (often referred to, including here, as "PC").
However, for many, including (2), no such equivalent can be found, and prosleptic syllogisms thus increased the inferential power of Peripatetic logic.
A more important limitation is how to balance the complexity of biogeographic models with the inferential power of the method (Ree and Sanmartín 2009).
Simulation results show that the proposed procedures have advantages over complete randomization with respect to both inferential (power) and ethical standpoints on average.
By the hybrid of disjunction and conjunction, for example, understanding ∨ and ∧ to have the inferential powers conferred on them by a particular logic, is meant a binary connective whose inferential powers are those shared ∧ and ∨. (See Rautenberg (1989) for this example, and Rautenberg (1991) and references therein for more in this vein).
Apart from the superhuman inferential powers attributed to the child, the problem highlighted by Wittgenstein is that no amount of observation can show, for example, that the relevant correlation is between "cow" and cow-individuals, and not between "cow" and B's cow-directed-actions, the universal cowhood, heifers rather than cows, etc. (cf. TSD 66d).
More recently, probabilistic model-based methods, namely the maximum likelihood (ML) and the Bayesian approaches have grown to prominence due to their statistical properties and inferential powers.
We describe the utility of spotted microarrays for these studies and highlight experimental design criteria that will maximize inferential and statistical power.
This latter rule was chosen to afford sufficient power for inferential data analysis to occur.
