MY464     
Introduction to Quantitative Methods for Media and Communications

This information is for the 2022/23 session.

Teacher responsible

Prof Patrick Sturgis COL.8.05

Availability

This course is available on the MPhil/PhD in Data, Networks and Society, MPhil/PhD in Media and Communications, MSc in Gender, Media and Culture, MSc in Global Media and Communications (LSE and Fudan), MSc in Global Media and Communications (LSE and UCT), MSc in Global Media and Communications (LSE and USC), MSc in Media and Communications, MSc in Media and Communications (Data and Society), MSc in Media and Communications (Media and Communications Governance), MSc in Media and Communications (Research), MSc in Media, Communication and Development, MSc in Politics and Communication and MSc in Strategic Communications. This course is not available as an outside option.

Students on the programmes listed above will be enrolled on this course when you register for MC4M1, MC4M2 or MC5M2. You must not register separately for MY464. It is not possible to take MY464 as a standalone course.

Course content

An intensive introduction to quantitative data analysis in the social sciences, with illustrative examples and class exercises drawn from the field of Media and Communications. The course is intended for students with no previous experience of quantitative methods or statistics. It covers the foundations of descriptive statistics and statistical estimation and inference. At the end of the course students will have an understanding of how to carry out and interpret significance tests and be able to implement univariate and bivariate data analysis and multiple linear regression. The seminars and computer exercises give 'hands-on' training in the application of statistical techniques to real social science research problems using the R computer package (no prior knowledge of R is necessary).

Teaching

This course is delivered through a combination of classes and lectures totalling a minimum of 30 hours across Michaelmas Term.

This course has a Reading Week in Week 6 of MT.

Formative coursework

Self-guided computer exercises implementing statistics covered in the lectures with weekly online homework on the material covered in the lectures and exercises.

Indicative reading

A course pack will be available for download online.


Additional reading: many introductory statistics books are available. But we particularly recommend Alan Agresti and Christine Franklin (2009) Statistics: The Art and Science of Learning from Data, and Alan Agresti and Barbara Finlay (2009, 4th edition) Statistical Methods for the Social Sciences.

Assessment

Exam (100%, duration: 2 hours) in the January exam period.

Key facts

Department: Methodology

Total students 2021/22: 1

Average class size 2021/22: 1

Controlled access 2021/22: No

Value: Non-credit bearing

Guidelines for interpreting course guide information

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.

Personal development skills

  • Application of numeracy skills
  • Specialist skills