MY456      Half Unit
Survey Methodology

This information is for the 2021/22 session.

Teacher responsible

Prof Patrick Sturgis COL.8.10

Availability

This course is available on the MSc in Applied Social Data Science, MSc in Human Geography and Urban Studies (Research), MSc in Marketing, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), MSc in Statistics (Financial Statistics) (Research), MSc in Statistics (Research), MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available as an outside option to students on other programmes where regulations permit.

This course is not controlled access. If you register for a place and meet the prerequisites, if any, you are likely to be given a place.

Pre-requisites

Knowledge of basic descriptive and inferential statistics, to the level of MY451 or equivalent. MY456 can also be taken in parallel with MY452L. Familiarity with notions of research design in the social sciences, to the level of MY400 or equivalent.

Course content

This course provides an introduction to the methodology of the design and analysis of social surveys. It is intended both for students who plan to design and collect their own surveys, and for those who need to understand and use data from existing large-scale surveys. Topics covered include concepts of target populations, survey estimation and inference, sampling error and nonsampling error; sample design and sampling theory; modes of data collection; web surveys; survey interviewing; cognitive processes in answering survey questions; design and evaluation of survey questions; nonresponse error; survey weights; analysis of data from complex surveys; accessing, preparing and working with secondary data from existing social surveys; comparative and longitudinal surveys. The course includes computer classes, using the statistical computer package Stata; no previous knowledge of Stata is required.

Teaching

This course is delivered through a combination of classes and lectures totalling a minimum of 20 hours across Lent Term. This year, some or all of this teaching may be delivered live or as short online videos. The classes will be live and delivered online or in person depending on access to campus in LT.

This course has a reading week in Week 6 of Lent Term.

Formative coursework

Exercises from some of the seminars and computer classes are submitted for feedback.

Indicative reading

Groves, R M, Fowler, F J, Couper, M P, Lepkowski, J M, Singer, E, and

Tourangeau, R (2009). Survey Methodology (2nd ed.). Wiley.

Assessment

Exam (50%, duration: 2 hours) in the summer exam period.
Project (50%, 2500 words).

The project is a report of approximately 20 to 30 pages, including tables and figures, or approximately 2,500 words, reporting the data analysis of a given research question and data set.

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Methodology

Total students 2020/21: 12

Average class size 2020/21: 12

Controlled access 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills