Statistical significance for measures of collocation strength
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Michael P. Oakes
Abstract
Of the commonly-used measures of lexical association or collocation strength, only some directly relate to statistical significance: the t-score, chi-squared, log-likelihood, the z-score and Fisher’s exact test. We describe each of these tests, and also describe a computer simulation by which we can derive confidence limits, and hence the statistical significance, of any measure of lexical association which is derived from the contingency table. We illustrate this approach using pointwise mutual information (PMI). We also describe how the Poisson distribution enables us to find the statistical significance of the raw frequency with which a collocation is found. We compare all these methods using collocates of “take”, namely “take up”, “take place”, “take advantage” and “take stock”.
Abstract
Of the commonly-used measures of lexical association or collocation strength, only some directly relate to statistical significance: the t-score, chi-squared, log-likelihood, the z-score and Fisher’s exact test. We describe each of these tests, and also describe a computer simulation by which we can derive confidence limits, and hence the statistical significance, of any measure of lexical association which is derived from the contingency table. We illustrate this approach using pointwise mutual information (PMI). We also describe how the Poisson distribution enables us to find the statistical significance of the raw frequency with which a collocation is found. We compare all these methods using collocates of “take”, namely “take up”, “take place”, “take advantage” and “take stock”.
Chapters in this book
- Prelim pages i
- Table of contents v
- Foreword vii
- Introduction 1
- Monocollocable words 9
- Translation asymmetries of multiword expressions in machine translation 23
- German constructional phrasemes and their Russian counterparts 43
- Computational phraseology and translation studies 65
- Computational extraction of formulaic sequences from corpora 83
- Computational phraseology discovery in corpora with the mwetoolkit 111
- Multiword expressions in comparable corpora 135
- Collecting collocations from general and specialised corpora 151
- What matters more: The size of the corpora or their quality? 177
- Statistical significance for measures of collocation strength 189
- Verbal collocations and pronominalisation 207
- Empirical variability of Italian multiword expressions as a useful feature for their categorisation 225
- Too big to fail but big enough to pay for their mistakes 247
- Multi-word patterns and networks 273
- How context determines meaning 297
- Detecting semantic difference 311
- Index 325
Chapters in this book
- Prelim pages i
- Table of contents v
- Foreword vii
- Introduction 1
- Monocollocable words 9
- Translation asymmetries of multiword expressions in machine translation 23
- German constructional phrasemes and their Russian counterparts 43
- Computational phraseology and translation studies 65
- Computational extraction of formulaic sequences from corpora 83
- Computational phraseology discovery in corpora with the mwetoolkit 111
- Multiword expressions in comparable corpora 135
- Collecting collocations from general and specialised corpora 151
- What matters more: The size of the corpora or their quality? 177
- Statistical significance for measures of collocation strength 189
- Verbal collocations and pronominalisation 207
- Empirical variability of Italian multiword expressions as a useful feature for their categorisation 225
- Too big to fail but big enough to pay for their mistakes 247
- Multi-word patterns and networks 273
- How context determines meaning 297
- Detecting semantic difference 311
- Index 325
