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 supplementary video content developed by Dr. Anwar Musah will be hosted on this webpage.

You can download the lecture notes and data sets for the practical 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

SOLUTIONS: [Week 1] | [Week 2] | [Week 3] | [Week 4]

Important note: The solutions will be made available each week after the seminars are completed.

Timetable and key locations

The lectures are held every week in-person on Tuesday from 11:00am to 01:00pm at the Medical Sciences and Anatomy Anatomy G29 JZ Young LT [MAP]

A series of 8 computer seminars will take place every week on Thursday from 09:00am to 02:00pm at the IOE Bedford Way (20) Building in Room 425 PC Lab 2 [MAP] and at the Bedford Way (26) Building in Room G11 [MAP].

All students have been allocated to one of 8 seminar groups (i.e., group 1, 2, 3, 4, 5, 6, 7, or 8). To avoid any confusion, please go to your group’s designated cluster room. Here are the precise location details for the lecture and seminar cluster rooms:

Group Location & Times
1 Room 425 PC Lab 2, IOE Bedford Way (20), 09:00am-10:00am
2 Room 425 PC Lab 2, IOE Bedford Way (20), 10:00am-11:00am
3 Room 425 PC Lab 2, IOE Bedford Way (20), 11:00am-12:00pm
4 Room G11 PC Cluster, Bedford Way (26), 11:00am-12:00pm
5 Room 425 PC Lab 2, IOE Bedford Way (20), 12:00pm-01:00pm
6 Room G11 PC Cluster, Bedford Way (26), 12:00pm-01:00pm
7 Room 425 PC Lab 2, IOE Bedford Way (20), 01:00pm-02:00pm
8 Room G11 PC Cluster, Bedford Way (26), 01:00pm-02:00pm

Seminar Facilitators: Mikaella Mavrogeni, Marta Fatica & Ricardo Mellado Labbe

Contact details

Anwar Musah | Lecturer in Social & Geographic Data Sciences
UCL Department of Geography
Room 115, North West Wing Building, WC1E 6BT
[Bookable ASF] | Email: