Crossword Solver > found answer > IDENTICALLY

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identically

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The answer IDENTICALLY has 3 possible clue(s) in existing crosswords.

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The word IDENTICALLY is VALID in some board games. Check IDENTICALLY in word games in Scrabble, Words With Friends, see scores, anagrams etc.

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Definitions of identically in various dictionaries:

adv - with complete identity

IDENTICALLY - In probability theory and statistics, a sequence or other collection of random variables is independent and identically distributed (i.i.d. or iid o...

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Possible Crossword Clues
How some twins dress
In exactly the same way
In the same way

Last Seen in these Crosswords & Puzzles
Sep 24 2018 The Times - Concise
Oct 22 2013 Universal
Nov 28 2011 The Guardian - Quick crossword

Possible Dictionary Clues
In an identical manner.
bidenticalb identical (-dn't-kl) adj. Exactly equal and alike. Of or relating to a twin or twins developed from the same fertilized ovum and having the same genetic makeup and closely similar appearance monozygotic.
with complete identity in an identical manner

Identically might refer to
In probability theory and statistics, a sequence or other collection of random variables is independent and identically distributed (i.i.d. or iid or IID) if each random variable has the same probability distribution as the others and all are mutually independent. Identically distributed, on its own, is often abbreviated ID. For uniformity, as both are discussed—and in widespread use—this article uses the visually cleaner IID in preference to the more prevalent convention i.i.d. * The annotation IID is particularly common in statistics, where observations in a sample are often assumed to be effectively IID for the purposes of statistical inference. The assumption (or requirement) that observations be IID tends to simplify the underlying mathematics of many statistical methods (see mathematical statistics and statistical theory). However, in practical applications of statistical modeling the assumption may or may not be realistic. To test how realistic the assumption is on a given data set, the autocorrelation can be computed, lag plots drawn or turning point test performed. * The generalization of exchangeable random variables is often sufficient and more easily met. * The assumption is important in the classical form of the central limit theorem, which states that the probability distribution of the sum (or average) of IID variables with finite variance approaches a normal distribution. * Often the IID assumption arises in the context of sequences of random variables. Then "independent and identically distributed" in part implies that an element in the sequence is independent of the random variables that came before it. In this way, an IID sequence is different from a Markov sequence, where the probability distribution for the nth random variable is a function of the previous random variable in the sequence (for a first order Markov sequence). An IID sequence does not imply the probabilities for all elements of the sample space or event space must be the same. For example, repeated throws of loaded dice will produce a sequence that is IID, despite the outcomes being biased.

Identically might refer to

In probability theory and statistics, a sequence or other collection of random variables is independent and identically distributed (i.i.d. or iid or IID) if each random variable has the same probability distribution as the others and all are mutually independent. Identically distributed, on its own, is often abbreviated ID. For uniformity, as both are discussed—and in widespread use—this article uses the visually cleaner IID in preference to the more prevalent convention i.i.d.
* The annotation IID is particularly common in statistics, where observations in a sample are often assumed to be effectively IID for the purposes of statistical inference. The assumption (or requirement) that observations be IID tends to simplify the underlying mathematics of many statistical methods (see mathematical statistics and statistical theory). However, in practical applications of statistical modeling the assumption may or may not be realistic. To test how realistic the assumption is on a given data set, the autocorrelation can be computed, lag plots drawn or turning point test performed.
* The generalization of exchangeable random variables is often sufficient and more easily met.
* The assumption is important in the classical form of the central limit theorem, which states that the probability distribution of the sum (or average) of IID variables with finite variance approaches a normal distribution.
* Often the IID assumption arises in the context of sequences of random variables. Then "independent and identically distributed" in part implies that an element in the sequence is independent of the random variables that came before it. In this way, an IID sequence is different from a Markov sequence, where the probability distribution for the nth random variable is a function of the previous random variable in the sequence (for a first order Markov sequence). An IID sequence does not imply the probabilities for all elements of the sample space or event space must be the same. For example, repeated throws of loaded dice will produce a sequence that is IID, despite the outcomes being biased.

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