Social Research Methods and the Internet II: Advanced Quantitative Analysis
Availability: Compulsory for OII MSc students. MSc students must take either this course or Advanced Quantitative Analysis. Students must agree with their Supervisor by Week 4 of Michaelmas Term which advanced course they wish to take.
Schedule: Hilary Term (Weeks 1-8). Mondays 14:15-16:15
Location: Seminar Room, Oxford Internet Institute, 1 St Giles, Oxford OX1 3JS.
The study of the Internet and related information and communication technologies (ICTs) provides new opportunities and challenges for the social sciences. Social Research Methods and the Internet provides students with the knowledge and skills to conduct and critically evaluate empirical research on the social implications of the Internet.
This course consists of five elements. All students must take Research Methods I and Statistics in Michaelmas term. In Hilary term all students must take Research Methods II and either Advanced Quantitative Analysis or Advanced Qualitative Analysis. In doing so, students by the end of the course will
understand the significance of alternative epistemological positions that provide the context for theory construction, research design, and the selection of appropriate analytical techniques;
develop an ability to conduct and manage all stages of the research process from developing research questions and hypotheses to presenting and disseminating findings;
understand how to devise appropriate research questions and research designs;
acquire analytical and interpretive skills for a range of quantitative and qualitative approaches to data collection;
understand how to use online tools and statistical techniques that support the research process (e.g. from statistical software to computer-assisted qualitative analyses).
A summary of the structure and assessment of Social Research Methods and the Internet is below. Full details of each element are provided in the relevant outline.
Weighting (% of final mark)
Research Methods I
3,000 word essay
3 hour exam
Research Methods II
3,000 word essay
Advanced Quantitive Analysis
3 hour exam
Advanced Qualitative Analysis
5,000 word report
Social Statistics introduces students to statistics for the social sciences, with an emphasis on application to research on the Internet and society. This course introduces students to the most important types of quantitative social science data: discrete, counted data and continuous data. The course is based on four themes.
The focus is on selection and interpretation of statistical techniques, reaching sensible conclusions, figuring out causality, and making decisions, combining graphical, exploratory, and confirmatory approaches in ways that suggest how to improve our understanding in the light of data.
This requires hands-on work with data through statistical software. All calculations are done using the software, not using hand calculations or calculators. Class lectures and discussions involve use of statistical software. Formative assignments require intensive statistical computing.
A hands-on approach to understanding data directs attention away from the formal, theoretical, mathematical properties of statistical estimators, which is sometimes an emphasis in statistics classes. The course emphasizes ability to interpret the substantive significance of graphical and numerical computer output.
The strong emphasis on data and use of software leads to a final theme: Data almost never come to researchers in a form appropriate for analysis; they must be converted into a suitable form. Thus the course teaches common forms of data manipulation and these are incorporated into the formative assignments.
The course is team taught during Hilary term. There is one, two-hour class each week. The format of the sessions includes lectures, student discussions and group work. All students are expected to attend all these sessions. In addition, a weekly two-hour surgery will be led by the teaching assistant to assist students in completing formative assignments. The surgery is optional but strongly recommended.
Model building and specification
Diagnosis and correction of problems: Outliers and nonlinearity
Diagnosis and correction of problems: Collinearity and heteroscedasticity
Logistic regression, II
Topics: Similarity matrices. Principal components analysis. Statistical power analysis
Review of Statistical Approaches and Illustrative Use Cases
Weekly formative assignments will be given during class. They will be due later in the week.
One three-hour exam in Week 9 of Hilary Term.
Any student failing this assessment will need to follow the rules set out in the OII Examining Conventions regarding re-sitting failed examinations.
(Please note that the assessment for this course is different for DPhil students. DPhil students should please refer to the Graduate Studies Handbook for guidance).
Students should note that over the course of the year, small changes may be made to the content, dates or teaching arrangements set out in this reading list, at the course provider's discretion. These changes will be communicated to students directly and will be noted on the internal course information website.