Skip to main content
Presented to you through Paradigm Publishing Services

John Benjamins Publishing Company

Visit our Partner Page See all our books
Chapter
Licensed
Unlicensed Requires Authentication

Chapter 5. Comparing two groups

t-test and Wilcoxon and Mann-Whitney tests for independent and dependent samples

Abstract

Do language learners who are taught by an innovative method show better results than those who are taught traditionally? Do speakers of one language variety speak faster than speakers of another variety? Do people of one gender use more hedging constructions than people of another? In this chapter, you will learn how to make such comparisons using the parametric t-test and the non-parametric Wilcoxon and Mann-Whitney tests for dependent and independent samples. You will learn how to compute the standard error and confidence intervals for the mean. The case studies will involve differences between high- and low-frequency nouns with regard to the number of associations that they trigger and their abstractness/concreteness scores.

Abstract

Do language learners who are taught by an innovative method show better results than those who are taught traditionally? Do speakers of one language variety speak faster than speakers of another variety? Do people of one gender use more hedging constructions than people of another? In this chapter, you will learn how to make such comparisons using the parametric t-test and the non-parametric Wilcoxon and Mann-Whitney tests for dependent and independent samples. You will learn how to compute the standard error and confidence intervals for the mean. The case studies will involve differences between high- and low-frequency nouns with regard to the number of associations that they trigger and their abstractness/concreteness scores.

Chapters in this book

  1. Prelim pages i
  2. Table of contents vii
  3. Acknowledgements xi
  4. Introduction 1
  5. Chapter 1. What is statistics? 7
  6. Chapter 2. Introduction to R 21
  7. Chapter 3. Descriptive statistics for quantitative variables 41
  8. Chapter 4. How to explore qualitative variables 69
  9. Chapter 5. Comparing two groups 87
  10. Chapter 6. Relationships between two quantitative variables 115
  11. Chapter 7. More on frequencies and reaction times 139
  12. Chapter 8. Finding differences between several groups 171
  13. Chapter 9. Measuring associations between two categorical variables 199
  14. Chapter 10. Association measures 223
  15. Chapter 11. Geographic variation of quite: Distinctive collexeme analysis 241
  16. Chapter 12. Probabilistic multifactorial grammar and lexicology 253
  17. Chapter 13. Multinomial (polytomous) logistic regression models of three and more near synonyms 277
  18. Chapter 14. Conditional inference trees and random forests 291
  19. Chapter 15. Behavioural profiles, distance metrics and cluster analysis 301
  20. Chapter 16. Introduction to Semantic Vector Spaces 323
  21. Chapter 17. Language and space 333
  22. Chapter 18. Multidimensional analysis of register variation 351
  23. Chapter 19. Exemplars, categories, prototypes 367
  24. Chapter 20. Constructional change and motion charts 387
  25. Epilogue 395
  26. The most important R objects and basic operations with them 397
  27. Main plotting functions and graphical parameters in R 409
  28. References 425
  29. Subject Index 433
  30. Index of R functions and packages 441
How to do Linguistics with R
This chapter is in the book How to do Linguistics with R
https://doi.org/10.1075/z.195.c5

Chapters in this book

  1. Prelim pages i
  2. Table of contents vii
  3. Acknowledgements xi
  4. Introduction 1
  5. Chapter 1. What is statistics? 7
  6. Chapter 2. Introduction to R 21
  7. Chapter 3. Descriptive statistics for quantitative variables 41
  8. Chapter 4. How to explore qualitative variables 69
  9. Chapter 5. Comparing two groups 87
  10. Chapter 6. Relationships between two quantitative variables 115
  11. Chapter 7. More on frequencies and reaction times 139
  12. Chapter 8. Finding differences between several groups 171
  13. Chapter 9. Measuring associations between two categorical variables 199
  14. Chapter 10. Association measures 223
  15. Chapter 11. Geographic variation of quite: Distinctive collexeme analysis 241
  16. Chapter 12. Probabilistic multifactorial grammar and lexicology 253
  17. Chapter 13. Multinomial (polytomous) logistic regression models of three and more near synonyms 277
  18. Chapter 14. Conditional inference trees and random forests 291
  19. Chapter 15. Behavioural profiles, distance metrics and cluster analysis 301
  20. Chapter 16. Introduction to Semantic Vector Spaces 323
  21. Chapter 17. Language and space 333
  22. Chapter 18. Multidimensional analysis of register variation 351
  23. Chapter 19. Exemplars, categories, prototypes 367
  24. Chapter 20. Constructional change and motion charts 387
  25. Epilogue 395
  26. The most important R objects and basic operations with them 397
  27. Main plotting functions and graphical parameters in R 409
  28. References 425
  29. Subject Index 433
  30. Index of R functions and packages 441
Downloaded on 19.4.2026 from https://www.degruyterbrill.com/document/doi/10.1075/z.195.c5/html
Scroll to top button