Welcome

Welcome to POLS0008: Introduction to Quantitative Research Methods. This is one of the first year core module for students enrolled on one of the degree programmes via the cross-faculty initiative [UCL Social Data Institute (SODA)]. This is open to students on the following degree programmes:

  • BSc Philosophy, Politics and Economics with Social Data Science
  • BA Geography with Social Data Science
  • BSc Population Health Science (Data Science)
  • BSc Social Sciences with Data Science

Description

This module will introduce students to the key tenets of quantitative methods in the social sciences. It assumes no knowledge of quantitative methods or statistical software. Hence, it caters for students from diverse disciplinary backgrounds and adopts a practical hands-on approach to learning, with tutor supported computer tutorials. The module covers descriptive statistics (central tendency and variation), data visualisation, data access, probability, sampling, hypothesis testing, inferential statistics and ends with an introduction to simple linear regression. Students will be introduced to the R statistical software and work with real-world data.

Structure

For the first four weeks, we will do a deep-dive covering all facets on Descriptive Statistics and R-programming - this will be taught by Dr. Anwar Musah. From Week 5 to 10, it will be focused on Inferential Statistics - this will be covered by Dr. Stephen Jivraj. Nearing the end of the course, you will be given an assignment i.e., a 3,000 word essay (counting 100% towards your final mark for this course) based on secondary analysis of survey data. This information will be introduced to you accordingly by both the module tutors to help you to mentally prepare for this moment.

All lecture notes, recommended reading and seminar learning materials as well as some supplementary video content will be hosted on this webpage.

You can download the lecture notes and data sets for the practical and seminar lesson from the table below.

Week Downloads Topics
1 [Lecture Notes] [Dataset] Understanding Data
2 [Lecture Notes] [Dataset] Examining Data I
3 [Lecture Notes] [Dataset] Examining Data II
4 [Lecture Notes] Sourcing Data

Important note: The solutions will be made available each week at the end of Thursday via email after the seminars are completed.

Timetable and key locations

The lectures are held every week in-person on Tuesday from 12:00pm to 02:00pm at the Roberts Building G06 Sir Ambrose Fleming LT [MAP]

A series of 9 computer seminars will take place every week on Thursday starting from 10:00am, up to 03:00pm. All students have been allocated to one of 9 seminar groups (i.e., group 1, 2, 3, 4, 5, 6, 7, 8 or 9). To avoid any confusion, please go to your group’s designated. You will be working together on the tasks and so please bring your laptops.

The table below highlights precise location for the seminars:

Seminar Location & Times
1 Tavistock Square (35) G01, 10:00am-11:00am
2 Cruciform Building Foyer 1.02 Seminar Room 2, 10:00am-11:00am
3 Cruciform Building Foyer 1.02 Seminar Room 2, 11:00am-12:00pm
4 Tavistock Square (35) G01, 11:00am-12:00pm
5 Tavistock Square (35) G01, 12:00pm-01:00pm
6 IOE Bedford Way (20) Room 790, 12:00pm-01:00pm
7 IOE Bedford Way (20) Room W2.08, 01:00pm-02:00pm
8 IOE Bedford Way (20) Room 790, 01:00pm-02:00pm
9 IOE Bedford Way (20) Room W2.08, 02:00pm-03:00pm

Postgraduate Seminar Facilitators: Ricardo Mellado Labbe, Rob Davidson & Tie Franco Brotto

Important note: Please bring your own laptops with you to the seminars on Thursday

Contact details

Anwar Musah | Lecturer in Social & Geographic Data Sciences
UCL Department of Geography
Room 115, North West Wing Building, WC1E 6BT
Office hours: TBC | Email: