Full Description
Traditional approaches focused on significance tests have often been difficult for linguistics researchers to visualise. Statistics in Corpus Linguistics Research: A New Approach breaks significance tests down for researchers in corpus linguistics and linguistic analysis, promoting a visual approach to understanding the performance of tests with real data, and demonstrating how to derive new confidence intervals and tests.
This fully revised second edition includes a brand-new chapter describing a novel extended 'MOVER' method to derive accurate confidence intervals for numerous properties. With sample datasets and easy-to-read visuals, this book focuses on practical issues, such as how to
pose meaningful research questions in terms of choice and constraint
employ confidence intervals correctly (including in graph plots)
select a significance test (and interpret its results)
construct confidence intervals for functions of independent proportions
measure the size of the effect of one variable on another or the similaritybetween two distributions; and
evaluate whether the results of two experiments significantly differ
Appropriate for anyone from the student just beginning their career to the seasoned researcher, this book is both a practical overview and valuable resource.
A website with downloadable resources for the calculations in this book is published at https://corplingstats.wordpress.com/siclr
Contents
Preface Acknowledgments A Note on Terminology and Notation PART 1: Motivations 1 What Might Corpora Tell Us About Language? PART 2: Designing Experiments With Corpora 2 The Idea of Corpus Experiments 3 That Vexed Problem of Choice 4 Choice Versus Meaning 5 Balanced Samples and Imagined Populations PART 3: Confidence Intervals and Significance Tests 6 Introducing Inferential Statistics 7 Plotting With Confidence 8 From Intervals to Tests 9 An Algebra of Intervals 10 Competition Between Choices Over Time 11 The Replication Crisis and the New Statistics 12 Choosing the Right Test PART 4: Effect Sizes and Meta-Tests 13 The Size of an Effect 14 Meta- Tests for Comparing Tables of Results PART 5: Statistical Solutions for Corpus Samples 15 Conducting Research With Imperfect Data 16 Adjusting Intervals for Random-Text Samples PART 6: Concluding Remarks 17 Plotting the Wilson Distribution 18 In Conclusion Appendix A The Interval Equality Principle Appendix B Pseudo-Code for Computational Procedures Glossary References Index
