For example, using Z-test of hypothesis in the following Figure.

Construction of confidence interval for , variance unknown
Example: Given xbar16 = 12.1, S = 2.225 develop a 95% confidence interval for Therefore P[11.31 ] 0.95 Again, notice the Duality between the test of hypothesis and confidence interval.

Consistent with this hypothesis, the specific ..

Find-S is used to find a maximally specific hypothesis, and the algorithm is defined as:

Version space learning - Wikipedia

From a deductive-logical point of view, the set of logicalconsequences of a given state description is a maximal consistent setof sentences of L(3): The set is consistent (consisting as itdoes of the logical consequences of a consistent sentence) andmaximal; no sentence of L(3) not implied by the set isconsistent with it. The state descriptions correspond to models, topoints in a logical space. A (symmetrical) probability on L(3)thus induces a normal measure on sets of models: Any assignment ofnon-negative numbers summing to one to the state descriptions ormodels fixes probabilities. In this finite case, the extent to whichevidence e supports a hypothesis h is the proportionof models for e in which h istrue. Deductively, e logically implies hif h is true in every model for e. Degree ofconfirmation is thus a metrical generalization of first-order logicalimplication.

Version space learning is a logical approach to machine ..

A very different approach is based on the idea that disproof need notbe demonstrative. The goal of this approach is to show that theexistence of an omni-God is so improbable that confident belief in thenon-existence of such a God is justified. Two such arguments arediscussed in detail below: the “low priors argument” andthe “decisive evidence argument”. Each of these argumentsemploys the same specific strategy, which is to argue that somealternative hypothesis to omni-theism is many times more probable thanomni-theism. This doesn’t imply that the alternative hypothesisis probably true, but it does imply that omni-theism is very probablyfalse. In the case of the second argument, the alternative hypothesis(aesthetic deism) is arguably a form of theism, and even in the caseof the first argument it is arguable that the alternative hypothesis(source physicalism) is compatible with some forms of theism (inparticular ones in which God is an emergent entity). This is not aproblem for either argument, however, precisely because both arearguments for local atheism instead of global atheism.

What is the calculated value suitable for testing the above hypothesis?

A possible definition of machine leaning is ..

Progol reduces this combinatorial explosion by using an alternative approach, called mode directed inverse entailment (MDIE). Inverse entailment is used to generate the most specific h that, together with background information, entails some observed data. General-to-specific search is then performed through a hypothesis space H bounded by the most specific hypothesis and constrained by the user-specified predicates.

For example, in many textbooks you find the authors double the p-value to compare it with  when dealing with the two-sided test of hypotheses.

Maximum parsimony (phylogenetics) - Wikipedia

15, No.3, 131-135, 1988.
Good Ph.., , Springer Verlag, 1999.
A p-value is a measure of how much evidence you have against the null hypothesis.

Find-S is guaranteed to output the most specific hypothesis in H consistent ..

Random effects structure for confirmatory hypothesis ..

Intuitively we know that a hypothesis hi is more general than hj if every instance that hj classifies as positive, hi also classifies as positive, and hi classifies instances as positive that hj does not.

Large values of the F statistic lead to a rejection of the “homogeneity of variance” null hypothesis

Since the P-value in a test of hypothesis is based on the specific ..

More fully, the user specifies H by stating predicates, functions, and forms of arguments allowed for each. Progol then uses a sequential covering algorithm: for each 〈xi, f(xi)〉 not covered by the learned rules, find the most specific hypothesis hi such that B ∧ hixi entails f(xi) (although it actually only considers a k-step entailment), and then conduct a general-to-specific search of H, bounded by the specific hypothesis hi, choosing a hypothesis with a minimum description length, and then finally removes the positive examples covered by this new hypothesis.