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A consistency proof is a mathematical proof that a particular theory is consistent. [8] The early development of mathematical proof theory was driven by the desire to provide finitary consistency proofs for all of mathematics as part of Hilbert's program .
In statistics, consistency of procedures, such as computing confidence intervals or conducting hypothesis tests, is a desired property of their behaviour as the number of items in the data set to which they are applied increases indefinitely.
In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints , cascades , triggers , and any combination thereof.
Wikipedia:Consistency proposal, a failed 2006 proposal for a consistency guideline for facts in articles (formerly at Wikipedia:Consistency) Topics referred to by the same term This page is a list of project pages associated with the same title or shortcut.
In this way one would obtain a sequence of estimates indexed by n, and consistency is a property of what occurs as the sample size “grows to infinity”. If the sequence of estimates can be mathematically shown to converge in probability to the true value θ 0 , it is called a consistent estimator; otherwise the estimator is said to be ...
Internal consistency is usually measured with Cronbach's alpha, a statistic calculated from the pairwise correlations between items. Internal consistency ranges between negative infinity and one. Coefficient alpha will be negative whenever there is greater within-subject variability than between-subject variability.
The most common internal consistency measure is Cronbach's alpha, which is usually interpreted as the mean of all possible split-half coefficients. [9] Cronbach's alpha is a generalization of an earlier form of estimating internal consistency, Kuder–Richardson Formula 20. [9]
Eventual consistency is a weak guarantee – most stronger models, like linearizability, are trivially eventually consistent. Eventually-consistent services are often classified as providing BASE semantics (basically-available, soft-state, eventual consistency), in contrast to traditional ACID (atomicity, consistency, isolation, durability).