Statistics in Language Research
eBook - PDF

Statistics in Language Research

Analysis of Variance

  1. 276 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Statistics in Language Research

Analysis of Variance

About this book

Statistics in Language Research gives a non-technical but more or less complete treatment of Analysis of Variance (ANOVA) for language researchers. ANOVA is the most frequently used technique when handling the outcomes of research designs with more than two treatments or groups. This technique is used in all parts of linguistics which deal with observations obtained in survey studies and in (quasi-)experimental research, like applied linguistics, psycholinguistics, sociolinguistics, language and speech pathology and phonetics. Most statistical textbooks in the social sciences take examples typical of their own field and, in addition, omit subjects which are particularly relevant for language researchers, like power analysis, quasi F, F1, F2 and minF'.

This book offers a thorough introduction to the basic principles of analysis of variance, based on examples taken from language research, and goes beyond the conventional topics treated in introductory textbooks, as it covers topics like 'violations of assumptions', 'missing data', 'problems in repeated measures designs', 'alternatives to analysis of variance' (such as randomization tests and multilevel analysis). Each chapter consists of four sections: treatment of the subject under discussion, a summary of relevant terms and concepts, a section devoted to reporting statistics, and finally an exercise section. After the first introductory chapter, in which fundamental concepts like 'variables', 'cases' and SPSS data formats are presented, the book continues with two 'refreshment' chapters, in which the principles of statistical testing are revised, focusing on the well-known t test. These chapters also deal with the essential, but often neglected concepts of 'statistical power' and 'sample size'. In every chapter examples of SPSS input and output are given.

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Information

Year
2010
Print ISBN
9783110185805
eBook ISBN
9783110877809

Table of contents

  1. Acknowledgements
  2. 1. Language research and statistics
  3. 1.1. Statistics and analysis of variance in language research
  4. 1.2. Variables
  5. 1.3. Designs
  6. 1.4. Statistical packages
  7. 2. Basic statistical procedures: one sample
  8. 2.1. Preview
  9. 2.2. Sampling variability
  10. 2.3. Hypothesis testing: one sample
  11. 2.4. The t distribution
  12. 2.5. Statistical power
  13. 2.6. Determining the sample size needed
  14. 2.7. Suggestions for statistical reporting
  15. 2.8. Terms and concepts
  16. 2.9. Exercises
  17. 3. Basic statistical procedures: two samples
  18. 3.1. Preview
  19. 3.2. Hypothesis testing with two samples
  20. 3.3. Dependent samples and the t test
  21. 3.4. t tests in SPSS
  22. 3.5. Comparing two proportions
  23. 3.6. Statistical power
  24. 3.7. How to determine the sample size
  25. 3.8. Suggestions for statistical reporting
  26. 3.9. Terms and concepts
  27. 3.10. Exercises
  28. 4. Principles of analysis of variance
  29. 4.1. Preview
  30. 4.2. A simple example
  31. 4.3. One-way analysis of variance
  32. 4.4. Testing effects: the F distribution
  33. 4.5. One-way analysis of variance in SPSS
  34. 4.6. Post hoc comparisons
  35. 4.7. Determining sample size
  36. 4.8. Power post hoc
  37. 4.9. Suggestions for statistical reporting
  38. 4.10. Terms and concepts
  39. 4.11. Exercises
  40. 5. Multifactorial designs
  41. 5.1. Preview
  42. 5.2. Multifactorial designs and interaction
  43. 5.3. Random and fixed factors
  44. 5.4. Testing effects in a two-factor design
  45. 5.5. Alternatives to testing effects in mixed designs
  46. 5.6. The interpretation of interactions
  47. 5.7. Summary of the procedure
  48. 5.8. Other design types
  49. 5.9. A hierarchical three-factor design
  50. 5.10. Analysis of covariance
  51. 5.11. Suggestions for statistical reporting
  52. 5.12. Terms and concepts
  53. 5.13. Exercises
  54. 6. Additional tests and indices in analysis of variance
  55. 6.1. Preview
  56. 6.2. Simple main effects
  57. 6.3. Post hoc comparisons in multifactorial designs
  58. 6.4. Contrasts
  59. 6.5. Effect size and strength of association
  60. 6.6. Reporting analysis of variance
  61. 6.7. Suggestions for statistical reporting
  62. 6.8. Terms and concepts
  63. 6.9. Exercises
  64. 7. Violations of assumptions in factorial designs and unbalanced designs
  65. 7.1. Preview
  66. 7.2. Assumptions in analysis of variance
  67. 7.3. Normality of variances and homogeneity
  68. 7.4. The impact of transformations
  69. 7.5. Scale of measurement and analysis of variance
  70. 7.6. Unbalanced designs and regression analysis
  71. 7.7. Suggestions for statistical reporting
  72. 7.8. Terms and concepts
  73. 7.9. Exercises
  74. 8. Repeated measures designs
  75. 8.1. Preview
  76. 8.2. Properties of within subjects-designs
  77. 8.3. A univariate analysis of a repeated measures design
  78. 8.4. Assumptions in repeated measures design
  79. 8.5. The interaction between subjects and a within-subject factor
  80. 8.6. Strange F ratios: testing hypotheses made difficult
  81. 8.7. Multivariate analysis in repeated measures design
  82. 8.8. Genuine multivariate analysis
  83. 8.9. Two within-subject factors
  84. 8.10. Post hoc comparisons
  85. 8.11. A split-plot design: within- and between-subject factors
  86. 8.12. Missing data
  87. 8.13. Suggestions for statistical reporting
  88. 8.14. Terms and concepts
  89. 8.15. Exercises
  90. 9. Alternative estimation procedures and missing data
  91. 9.1. Preview
  92. 9.2. Likelihood estimation
  93. 9.3. Likelihood estimation in analysis of variance
  94. 9.4. Two examples: a balanced and an unbalanced design
  95. 9.5. Imputation procedures for missing data
  96. 9.6. Suggestions for statistical reporting
  97. 9.7. Terms and concepts
  98. 9.8. Exercises
  99. 10. Alternatives to analysis of variance
  100. 10.1. Preview
  101. 10.2. Randomization tests
  102. 10.3. Bootstrapping
  103. 10.4. Multilevel analysis
  104. 10.5. Suggestions for statistical reporting
  105. 10.6. Terms and concepts
  106. 10.7. Exercises
  107. References
  108. Appendices
  109. A: Key to the exercises
  110. B: Matrix Algebra
  111. C: Statistical tables
  112. Index

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