HSS8005 : Introduction to Quantitative Methods

Semester 2 Credit Value: 20
ECTS Credits: 10.0


This module aims to develop students’ understanding of the general principles and design of statistical analysis in addition to training students in the use of the statistical package SPSS. Students will learn about some of the statistical techniques used in Social Science, with options to take more advanced streams later in the course.
- Students will be introduced to the concepts underlying the statistical analysis of quantitative data in the Social Sciences
- Students will learn about which statistical techniques for univariate, bivariate and multivariate data analysis of cross-sectional data
- Students will develop a critical understanding of the statistical methods they will learn about
- Students will learn about and use the statistical packages – primarily SPSS
- Optional advanced streams include: multivariate analysis, spatial analysis, quantitative linguistics, longitudinal analysis

Outline Of Syllabus

The syllabus comprises the following elements:

Outline of syllabus
1. Overview of stats, why statistics and introduction to statistical packages
2. Descriptive statistics, understanding and presenting data visually
3. Parameters, populations/sampling, normal distribution (standard errors), confidence intervals, hypothesis testing
4. Comparing means
5. Correlation
6. Regression (intro to multiple regression optional)

Optional Streams
1. Multivariate analysis
2. Longitudinal analysis
3. GIS
4. Quantitative Linguistics

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion1401:00140:00Independent assessment preparation
Guided Independent StudyDirected research and reading201:0020:00Online content
Guided Independent StudySkills practice201:0020:00SPSS
Scheduled Learning And Teaching ActivitiesSmall group teaching102:0020:00Seminars/group work
Teaching Rationale And Relationship

The module uses a blended learning approach, providing directed online activities and reading. Videos are used to introduce and guide students through statistical concepts and principles, as well as the critical engagement aspects (i.e. identifying and critically assessing how statistics are used in the social sciences). This is supplemented by readings and practical tasks and activities. Here, students will be able to further explore concepts and principles, and test their knowledge with regular and varied multiple choice question (MCQs) tasks. These tasks are computerised and automated, and every answer (including the correct answer) will provide students with feedback (and suggestions for further review, where appropriate).

Given the practical nature of statistical analysis, and that a core requirement of this module is to equip students with the knowledge and skills to manage, manipulate, analyse, and interpret (and to an extent, visually present) data, most sections will include a practical element. This practical element will provide students with capability to use a statistical software package. The practical element of this module will include face-to-face seminars/webinar sessions where small groups of students will be able to interact with one another and a member of teaching staff and complete activities.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Description Length Semester When Set Percentage Comment
PC Examination602M1020 unseen MCQ's on Blackboard (Timed)
Other Assessment
Description Semester When Set Percentage Comment
Written exercise2A503000 word report
Written exercise2A401500 word critique of research extracts (Short essay questions)
Formative Assessments
Description Semester When Set Comment
Computer assessment2MMCQ allow students to test their knowledge across every session and include feedback on how to attain correct answers in the future.
Prob solv exercises2MGroup work - report analysis, which allows students to complete their summative assessments.
Assessment Rationale And Relationship

The module’s assessment strategy aims to provide early opportunities for students to self-check, as well as demonstrate their knowledge, and to receive formative feedback which can feed forward into the later assessments. MCQs are designed to assess how well students understand the statistical concepts and principles. MCQs will be used in both task-based learning in each section, as well as two separate, short, assessed pieces. The report is designed to equip students with an idea of how to embed statistical analysis into the research process, from identifying which data to use to address the research question and managing that data, to choosing the correct test, interpreting the results, and presenting those results visually and analytically/critically. The critical essay is designed to assess how well candidates understand the advantages and limitations of statistical analysis in published works and their own work (i.e. the report).

Reading Lists