MEASURING THE SOCIAL WORLD: QUANTITATIVE METHODS - 2025/6
Module code: SOC1050
Module Overview
This foundation module is design to introduce students to the statistical techniques necessary for implementing and critically evaluating social research. Emphasis will be put on when and how data is collected, how to use basic statistical techniques to analyse the data appropriately, and how to interpret results, rather than on theoretical derivations. A familiarity with R will also be acquired during practical work.
Module provider
Sociology
Module Leader
BERLUSCONI Giulia (Sociology)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 4
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 95
Lecture Hours: 22
Laboratory Hours: 11
Captured Content: 22
Module Availability
Semester 2
Prerequisites / Co-requisites
N/A
Module content
Indicative content includes:
• The role of statistics in modern societies;
• The ethics of quantitative research;
• Surveys and questionnaire design;
• Sampling theory and practice;
• Levels of measurement and types of variable;
• Estimators of central tendency and dispersion;
• Statistical inference, estimation and hypothesis testing.
Assessment pattern
Assessment type | Unit of assessment | Weighting |
---|---|---|
School-timetabled exam/test | TEST (1 HOUR) | 40 |
Examination | SHORT ANSWER AND MCQ EXAM (1 HOUR) | 60 |
Alternative Assessment
N/A
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate that they have (a) understood the basic concepts used to describe the characteristics of population and survey data, and (b) know how to choose appropriate statistical techniques to test hypotheses and interpret the associated statistical outputs.
The summative assessment for this module consists of a one-hour class test on descriptive statistics, and a one-hour exam on hypothesis testing.
The formative assessment includes verbal feedback in class, when students will have the opportunity to work on class exercises and receive feedback on how they are progressing.
Module aims
- Introduce students to the statistical techniques required to conduct and critically evaluate social research
- Provide an understanding of when and how to use particular statistical techniques, including hand on experience with R
- Offer a conceptual and theoretical outline of inferential statistics
Learning outcomes
Attributes Developed | ||
001 | Design a quantitative study, collect relevant data, and analyse them using univariate and bivariate statistical tehniques | |
002 | Have an understanding of the use of computer software for statistical analysis | PT |
003 | Have a thorough grounding in descriptive and basic inferential statistical techniques |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to encourage students to understand the importance of using statistics in social research as a way of describing and explaining social life.
The learning and teaching methods include:
• Lectures based around the theoretical and practical importance of statistics and how they are commonly applied to social research;
• Laboratory classes where students will familiarise themselves with the technical and practical issues using R to analyse quantitative data.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: SOC1050
Other information
N/A
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.