| CODE | DOC6049 | ||||||
| TITLE | Statistical Methods for the Humanities and the Social Sciences | ||||||
| UM LEVEL | D - Doctoral Workshops/Symposium | ||||||
| MQF LEVEL | Not Applicable | ||||||
| ECTS CREDITS | Not Applicable | ||||||
| DEPARTMENT | Doctoral School | ||||||
| DESCRIPTION | Statistical methods are an important part of the researcher’s toolbox, especially in cases where research is empirically grounded, and necessitates the description, interpretation and/or modelling of significant amounts of data. Recently, scholars in the humanities and social sciences – such as linguists, historians, archaeologists, literary theorists and practitioners in the burgeoning field of Digital Humanities – have turned increasingly to quantitative methods, to complement more established methods in these fields. This workshop focuses on how statistical methods can be used to make sense of data. It does not assume prior knowledge of statistics but seeks to give doctoral researchers a good overview of the following: 1. Organising data, identifying variables, and describing the trends they exhibit; 2. Constructing statistical models (especially the class of models subsumed under the heading of ‘Generalised Linear Models’), evaluating them and using them to make predictions; 3. Understanding the concept of statistical significance and the logic of hypothesis-testing. As well as introducing the above topics and discussing their theoretical underpinnings, an important aim of the workshop is to develop practical skills for data analysis. To this end, the workshop will also introduce the R language and associated packages for statistical analysis. Sessions will be divided into theoretical and practical components. Participants will be strongly encouraged to bring their own data for use during the practical sessions. Prior to the workshop, participants will be asked to give a brief description of their research, as well as the type of data they are working with. This will help the tutors develop the practical sessions to be maximally useful to participants. Outcomes: By the end of this workshop, doctoral researchers should: - distinguish types of variables and formulate empirical, testable hypotheses - identify the right statistical methods to apply to address specific research questions using different kinds of data - construct statistical models to address hypotheses or explore trends in large datasets - write simple R scripts for data analysis and visualisation of data - interpret statistical data - evaluate reports of empirical findings. |
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| ADDITIONAL NOTES | This workshop runs over three consecutive weeks and is split into different parts as follows: week 1 (3 + 3 + 1 hours), week 2 (2 hours), week 3 (4 + 3 + 2 hours). Attendance is required for all parts. This is a bring-your-laptop workshop and since there is a practical component, your laptop will need to have R and RStudio installed. Prior to the workshop, participants will be given clear instructions on how to install this software and what additional libraries they will need. All software used is freely available and/or open-source. Timetable Details - Please click here for further details. |
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| STUDY-UNIT TYPE | Workshop | ||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Albert Gatt 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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