MY451L      Half Unit
Introduction to Quantitative Analysis

This information is for the 2021/22 session.

Teacher responsible

Dr Marion Lieutaud

Availability

This course is available on the Global MSc in Management, Global MSc in Management (CEMS MiM), Global MSc in Management (MBA Exchange), MPhil/PhD in Demography/Population Studies, MSc in Applied Social Data Science, MSc in Comparative Politics, MSc in Conflict Studies, MSc in European and International Public Policy, MSc in European and International Public Policy (LSE and Bocconi), MSc in European and International Public Policy (LSE and Sciences Po), MSc in Gender (Research), MSc in Inequalities and Social Science, MSc in International Migration and Public Policy, MSc in International Migration and Public Policy (LSE and Sciences Po), MSc in International Social and Public Policy (Research), MSc in Public Administration and Government (LSE and Peking University), MSc in Public Policy and Administration and MSc in Social Research Methods. This course is available with permission as an outside option to students on other programmes where regulations permit.

The course is also available to research students as MY551.

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.

Course content

An intensive introduction to quantitative data analysis in the social sciences. 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 should be able to carry out univariate and bivariate data analysis and have an appreciation of multiple linear regression. The computer exercises give 'hands-on' training in the application of statistical techniques to real social science research problems. No prior knowledge of any statistical software is necessary.

Teaching

This course is delivered through a combination of short online recorded films for the lectures and live classes, which will be delivered face-to-face where feasible, or online where not. Combined hours across lectures and classes will be equivalent to a minimum of 30 hours face-to-face teaching.

The course runs twice per year: in MT (MY451M) and again in LT (MY451L). The content of the course, and the method of assessment, is exactly the same in each term.

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

Formative coursework

Self-guided computer exercises to be completed before weekly classes for discussion.

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. Pearson Education. Or Alan Agresti and Barbara Finlay (2009, 4th edition) Statistical Methods for the Social Sciences. Pearson Education (note that the second book is more advanced and is particularly useful if you are planning to take MY451 and MY452.

Assessment

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

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: 60

Average class size 2020/21: 15

Controlled access 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Application of numeracy skills
  • Specialist skills