USING R IN THE RESEARCH BY FUTURE PHILOLOGISTS

Authors

DOI:

https://doi.org/10.33407/itlt.v66i4.2196

Keywords:

R statistical software environment, corpus of academic speech, hedges, the Kolmogorov-Smirnov test, the Mann-Whitney U Test

Abstract

Corpus linguistics is a newly emerging field of study in applied linguistics that deals with construction, processing, and exploitation of text corpora. To date, a high-quality analysis of vast amounts of empirical language data provided by computerized corpora is impossible without computer technologies and relevant statistical methods. Therefore, teaching future philologists to effectively apply statistical computer programs is an important stage in their research training. The article discusses the possibilities of using one of the leading in Western linguistics, but not well-known in Ukraine, software packages for statistical data analysis – R statistical software environment – in the research by future philologists. The paper reveals the advantages and disadvantages of this program in comparison with other similar software packages (SPSS and Statistica) and provides Internet links to R self-learn tutorials. The flexibility and efficacy of R for linguistic research are demonstrated on the example of a statistical analysis of the use of hedges in the corpus of academic speech. For novice philologists to properly understand the peculiarities of conducting a statistical linguistic experiment with R, a detailed description of each stage of the study is provided. The statistical verification of hedges in the speech of students and lecturers was carried out using such statistical methods as the Kolmogorov–Smirnov test and the Mann-Whitney U Test. The article presents the developed algorithms to calculate the specified tests applying the built-in commands and various specialized library functions, created by R user community to enhance the functionality of this statistical software. Each script for statistical calculations in R is accompanied by a detailed description and interpretation of the results obtained. Further study of the issue will involve a number of activities aimed at raising awareness and improving skills of future philologists in using R statistical software, which is important for their professional development as researchers.

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Author Biographies

Victoriia V. Zhukovska, Zhytomyr Ivan Franko State University, Zhytomyr

PhD in Philology, Associate Professor,Head of the Department of Cross-Cultural Communication and Applied Linguistics

Oleksandr O. Mosiiuk, Zhytomyr Ivan Franko State University, Zhytomyr

PhD in Pedagogics, Senior Lecturer, Department of Applied Mathematics and Computer Science

Veronika V. Komarenko, Zhytomyr Ivan Franko State University, Zhytomyr

Lecturer, Department of Cross-Cultural Communication and Applied Linguistics

References

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REFERENCES (TRANSLATED AND TRANSLITERATED)

L. A. Janda, Quantitative Methods in Cognitive Linguistics. An Introduction, Cognitive linguistics. The quantitative turn. The essential reader, Berlin : De Gruyter Mouton, 2013, (in English).

S. N. Buk, The Basics of Statistical Linguistics: educational method. manual, Lviv: Publishing Center of Ivan Franko National University of LNU, 2008, (in Ukrainian).

What is R? : [Online]. Available: https://www.r-project.org/about.html, (in English).

R resources (free courses, books, tutorials, & cheat sheets). [Online]. Available: https://paulvanderlaken.com/2017/08/10/r-resources-cheatsheets-tutorials-books/, (in English).

Why RStudio? [Online]. Available: https://www.rstudio.com/about/, (in English).

Michigan corpus of academic spoken English. [Online]. Available: https://quod.lib.umich.edu/m/ micase/, (in English).

D. Lakoff, Hedges: A study in meaning criteria and the logic of fuzzy concepts, Journal of philosophical logic, №. 2 (4), 1972, p. 458 - 508. (in English).

A. V. Yarkho, Referential hedging as an etiquette strategy in the discourse of an anglo-american scientific research paper: a contrastive analysis, Journal of Kharkiv National University named after V. N. Karazin, №930 Series «Romano-Germanic Philology. Methodology of Teaching Foreign Languages», 2010, issue 64, p. 82-90., (in Ukrainian).

V. V. Shiluk, Classification of means of expressing the position of the speaker in spoken communication: comparative analysis, Bulletin of Zhytomyr State University, issue 2 (80), 2015, p. 302 - 308, (in Ukrainian).

E. V. Sydorenko, Methods of mathematical processing in psychology, SPb: OOO “Rech”, 2000, (in Russian).

L. V. Shelekhova, Mathematical Methods in Pedagogy and Psychologists: in Schemes and Tables: Textbook, Maykop: ASU Publishing house, 2010, (in Russian).

V. V. Levitsky, Quantitative methods in linguistics, Chernivtsi: Ruta, 2004, (in Russian).

R. G. Piotrovsky, K. B. Bektaev, A. A. Piotrovskaya, Mathematical Linguistics: Textbook for pedagogical institutes, Moscow: «Higher School», 1977, (in Russian).

H. W. Lilliefors, On the Kolmogorov-Smirnov test for normality with mean and variance unknown, Journal of the American Statistical Association, vol. 62,1967, p. 399 - 402, (in English).

Package ‘nortest’. [Online]. Available: https://cran.r-project.org/web/packages/nortest/nortest.pdf, (in English).

R. M. Conroy, What hypotheses do “nonparametric” two-group tests actually test?, The Stata Journal, № 2, 2012, p. 182 - 190, (in English).

F. Wilcoxon, Individual comparisons by ranling methods, Biometrics Bull, vol. 1, 1945, p. 80 - 83, (in English).

H. B. Mann, D. R. Whitney, On a test of whether one of two random variables is stochastically larger than the other, Annals of Mathematical Statistics, vol. 18, № 1, 1947, p. 50 - 60, (in English).

A. B. Shipunov, A. I. Korobeinikov, E. M. Baldin, Analysis of data with R (II). [Online]. Available: http://www.inp.nsk.su/~baldin/DataAnalysis/R/R-05-2var.pdf, (in Russian).

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Published

2018-09-30

How to Cite

[1]
V. V. Zhukovska, O. O. Mosiiuk, and V. V. Komarenko, “USING R IN THE RESEARCH BY FUTURE PHILOLOGISTS”, ITLT, vol. 66, no. 4, pp. 272–285, Sep. 2018.

Issue

Vol. 66 No. 4 (2018)

Section

Post-graduate teachers and scientists training on the use of ICT

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