
ARF – Average Reduced Frequency _{[ statistics ]}
a modified frequency which prevents the result to be excessively influenced by one part of the corpus (e.g. one or more documents) which contains a high concentration of the token. If the token is evenly distributed across the corpus, ARF and frequency per million will be comparable. see also ARF definition 
freq/mill – frequency per million _{[ statistics ]}
a number of occurrences (hits) of an item normalised per million, also called as i.p.m. (instances per million). It is used to compare frequencies between corpora of different sizes. number of hits : corpus size in millions of tokens = frequency per million Example: A token found 10 times in a corpus of 1 million tokens will have a frequency per million equal to 10. A token found 100 times in a corpus of 100 million tokens will have a frequency per million equal to 1. The second token is less frequent. see also Statistics in Sketch Engine Frequency per million Average Reduced Frequency 
likelihood _{[ statistics ]}
a function of parameters of a statistical model, it plays a key role in statistical inference and is the basis for the loglikelihood function. see Statistics in Sketch Engine 
loglikelihood _{[ statistics ]}
one of the functions used in computed statistics of Sketch Engine. It is the association measures based on the likelihood function, using in tests for significance (see the loglikelihood calculator and more details) 
logDice _{[ statistics ]}
a statistic measure for identifying collocation candidates which is used in the word sketch feature. It is based only on a frequency of words and and the bigram , it is not affected by a size of the corpus See logDice in Statistics used in Sketch Engine. 
MI Score _{[ statistics ]}
The Mutual Information score expresses the extent to which words cooccur compared the number of times they appear separately. MI Score is affected strongly by the frequency, lowfrequency words tend to reach a high MI score which may be misleading. This is why Sketch Engine allows setting a limit and words with a frequency below this limit will not be included in the calculation. In most cases Tscore is more useful than MI score. see Concordance  Collocations see Statistics in Sketch Engine compare Tscore 
minimum sensitivity _{[ statistics ]}
a statistics measure similar to logDice which is the minimum of the two following numbers:
 the number of cooccurrences divided by the frequency of the collocate
 the number of cooccurrences divided by the frequency of the node word
The minimum sensitivity number grows with a high number of cooccurrences and falls with a high number of occurrences of the individual words (node word or collocate).

overall score _{[ statistics ]}
score of the relation based on logDice in word sketches. The score is displayed in the header of each column of the relation. 
salience _{[ statistics ]}
a statistical measure of the significance of a specific token in the given context. This is measured with logDice, for more information, see section 3 of Statistics used in Sketch Engine) 
simple math _{[ statistics ]}
the simple formula used for the computation and identification of terms and keywords. see Simple math. 
Tscore _{[ statistics ]}
Tscore expresses the certainty with which we can argue that there is an association between the words, i.e. their cooccurrence is not random. The value is affected by the frequency of the whole collocation which is why very frequent word combinations tend to reach a Tscore high value despite not being significant as collocations. In most cases, Tscore is more reliable or more useful than MI Score. see Concordance  collocations see Statistics in Sketch Engine compare MI Score