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HASK | COLLOCATION DATABASES
Citation Please cite this paper in publications using HASK for the BNC: Pezik, Piotr. Graph-Based Analysis of Collocational Profiles. In Phraseologie Im Wörterbuch Und Korpus (Phraseology in Dictionaries and Corpora), edited by Vida Jesenšek and Peter Grzybek, 227–43. ZORA 97. Maribor, Bielsko‑Biała, Budapest, Kansas, Praha: Filozofska fakuteta, 2014.
150,045entries containing2,875,407combinations...
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Part of speech:
Collocate's part of speech:
excelSpreadsheet
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TTEST
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# Collocate POS A TTEST MI3 CHISQ JD R AWT fAWT Details Equivalents
1. change change
changed
changing 		Verb 28 4.76 12.92 224.54 0.8 23 4,273,241 12.72
2. enjoy enjoy
enjoyed
enjoying 		Verb 9 2.49 8.91 36.96 0.64 8 14,929,491 3.64
3. suit suit
suits 		Verb 7 2.48 9.61 98.4 0.53 5 24,433,368 2.22
4. alter alter
altered
altering 		Verb 6 2.27 8.97 72.09 0.53 5 19,529,869 2.78
5. affect affect
affected 		Verb 6 1.9 7.32 16 0.53 5 15,248,259 3.56
6. adopt adopt
adopted 		Verb 5 1.83 7.09 18.2 0.56 5 16,137,845 3.37
7. improve improve
improving 		Verb 5 1.72 6.76 12.79 0.48 4 17,496,472 3.11
8. maintain maintain Verb 5 1.65 6.58 10.47 0.48 4 16,498,611 3.29
9. lead lead
leading
leads
led 		Verb 8 1.6 7.2 5.87 0.57 6 18,470,779 2.94
10. live live
lived
living 		Verb 7 1.41 6.71 4.27 0.58 6 11,214,519 4.85
11. become became
become
becoming 		Verb 5 -0.92 4.15 0.6 0.56 5 17,007,616 3.2
12. may may Verb 7 -1.91 4.83 2.13 0.63 7 16,606,149 3.27
13. make made
make
making 		Verb 10 -3.92 5.48 6.97 0.66 9 7,652,916 7.1
14. can can Verb 12 -4.61 5.95 9.33 0.7 11 9,958,853 5.46
15. would would Verb 8 -8.21 4.04 17.69 0.66 8 11,100,783 4.9
16. will will Verb 5 -10.16 2.17 19.02 0.56 5 14,240,784 3.82
17. do did
do
does
doing 		Verb 8 -17.32 3.17 44.02 0.54 6 20,066,525 2.71
18. have had
has
have
having 		Verb 34 -17.48 8.18 85.23 0.79 26 3,482,370 15.61
19. be 're
's
am
are
be
been
being
is
was
were 		Verb 112 -30.88 11.64 364.53 0.88 59 1,143,125 47.55
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