| CODE | LIN2032 | |||||||||
| TITLE | Quantitative Research Methods in Linguistics | |||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | |||||||||
| MQF LEVEL | 5 | |||||||||
| ECTS CREDITS | 4 | |||||||||
| DEPARTMENT | Institute of Linguistics and Language Technology | |||||||||
| DESCRIPTION | This study-unit will introduce students to basic statistical techniques for use in experimental and data-driven analysis of Natural Language, complementing the grounding that students acquire in other methodologies (such as the collection and analysis of child language data, corpora and speech) through other units. Quantitative techniques are becoming increasingly central to Linguistics, where theoretical generalisations are increasingly reliant on empirical data. The study-unit will focus on the following areas: 1. An introduction to basic probability theory; 2. The notion of a distribution, with particular reference to some fundamental distributions such as the normal and zipfian distributions; 3. Basic measures of central tendency and dispersion in samples and populations; 4. Correlation and regression techniques; 5. Basic hypothesis testing methods (chi-square tests, t-test). Throughout, an emphasis will be placed on practical applications, with students being given the opportunity to deploy their newly acquired skills to analyse linguistic data. An important feature of this study-unit is that it also introduces students to the use of software packages for statistical analysis, such as R. Study-unit Aims: The unit aims to give students a grounding in basic techniques for data analysis. In addition, a strong practical component is intended to help the students learn how to deploy the techniques to answer specific questions about trends and distributions observed in large data samples. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - learn about basic statistical concepts, especially probability, distributions, and measures of central tendency and dispersion; - identify the correct procedures for data analysis in specific instances; - formulate precise hypotheses and draw conclusions based on tests which falsify the corresponding null hypothesis. 2. Skills: By the end of the study-unit the student will be able to: - use appropriate software packages for statistical analysis; - analyse linguistic using appropriate statistical techniques. Main Text/s and any supplementary readings: - S. Gries (2009). Statistics for linguistics with R: a practical introduction. Berlin & New York: Mouton de Gruyter Additional texts: - A. Woods, P. Fletcher and A. Hughes (1986). Statistics in Language Studies. Cambridge: Cambridge University Press - R. H. Baayen (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics using R. Cambridge: Cambridge University Press |
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| STUDY-UNIT TYPE | Lecture and Practicum | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Paul Marty Patrizia Paggio |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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