Dr Sally Stares

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.

The course is intended for students with no previous experience of quantitative methods or statistics. It is designed to equip students to understand and critically reflect on reporting of commonly encountered quantitative analyses as presented, for example, in news reports, annual reports, opinion polls and academic articles in the field of Media and Communications. It covers the foundations of descriptive statistics and statistical estimation and inference, including tests of statistical significance, via a range of univariate and bivariate data analyses, and multiple linear regression. The seminars and practical exercises provide introductory skills training, applying these techniques to real social science data and interpreting their results.

This course is delivered through a combination of seminars and lectures totalling 15 hours across the Autumn Term.

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

Self-guided practical exercises and readings to be completed before seminars for discussion, and Moodle (online) quizzes to support learning.

A course pack will be available for download online to support the technical content of the course. Many introductory statistics books are also available; 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. Michael Blastland and Andrew Dilnot’s (2008) The Tiger That Isn’t: Seeing Through a World of Numbers provides an indication of ‘critical’ element of the course content.

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