ULMS Electronic Module Catalogue

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Code ULMS603
Coordinator Professor D Jayawarna
Strategy, IB and Entrepreneurship
Year CATS Level Semester CATS Value
Session 2023-24 Level 7 FHEQ First Semester 40

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):


Modules for which this module is a pre-requisite:


Programme(s) (including Year of Study) to which this module is available on a required basis:


Programme(s) (including Year of Study) to which this module is available on an optional basis:


Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 12



Timetable (if known)              
Private Study 370


EXAM Duration Timing
% of
Penalty for late
CONTINUOUS Duration Timing
% of
Penalty for late
Independent Research Report There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When): Semester 1    30       
Evaluation of secondary data, data analysis and interpretation There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedu    70       


This module aims to:

Introduce the general principles of quantitative research design;

Explore, critically, a range of quantitative research designs and design related issues that the researchers likely to encounter in developing an effective quantitative research programme, eg response bias, sampling related errors, data validity and reliability, develop the research instruments;

Introduce a range of descriptive and inferential quantitative methods, their underlying principles, suitability and purpose and the research designs where they are likely to be employed;

Enable the students to obtain working knowledge of SPSS and an introduction to other popular statistical packages such as AMOS and STATA to handle survey data and to conduct, interpret and report quantitative data analyses;

Provide a knowledge to evaluate better the methods and statistical analysis from published research papers and reports;

Develop skills in accessing, downloading and a nalysing secondary data;

Discuss the issues related to longitudinal data analysis and interpretation.

Learning Outcomes

(LO1) Understand the overall process of quantitative research;

(LO2) Demonstrate a good understanding of the concepts of bias, validity, reliability and generalisability within quantitative research;

(LO3)  Formulate and operationalise a research question/hypothesis;

(LO4) Understand the needs for data, data types and sampling techniques

(LO5) Demonstrate knowledge and understanding of how analysis of quantitative research would be undertaken by selecting appropriate techniques and showing awareness of the assumptions on which they are based;

(LO6) Use statistical software packages (SPSS) for data analysis;

(LO7) Evaluate different statistical software as related to the research of interest and the type of analysis;

(LO8) Report essential findings and provide an accurate interpretation of results;

(LO9) Critically evaluate research publications from a methodological and statistical perspective;

(S1) Communication skills. Students will have opportunities to develop written and oral communication skills through group discussions, in-class presentations and coursework. This will be assessed by written assignments

(S2) Problem solving skills. Students will be challenged to think critically about organisational issues and dilemmas. They will do this by gathering and synthesising information, analysing alternative perspectives and options and presenting a considered opinion or course of action in their course assessment.

(S3) IT skills. Students will have opportunities to improve their ICT skills. Students will demonstrate skills in the use of software applications including word processing, visual presentations, data bases, spreadsheets and using the internet for information searches in the course of researching and presenting coursework.

(S4) Organisational skills. This applies to all modules of the programme and is relevant for planning scheduled work and meeting assessment deadlines. This will be evident in the students’ independent management of their assignments and coursework and by meeting coursework deadlines.

Teaching and Learning Strategies

12 hours lectures
12 hours seminars
6 hours drop-in
370 hours self-directed learning



Introduction to quantitative research – qualitative vs. quantitative research, quantitative research designs and research process, key concepts;

Developing a research framework, formulating research questions/hypotheses, hypotheses testing;

Sampling, variables, types of data, measurement process, questionnaire/experiment design, data distributions, survey administration, data coding;

Data analysis, reporting and interpretation – descriptive statistics, testing for assumptions, bivariate statistics (ANOVA, t-tests, non-parametric tests including chi-square), graphs, correlation;

Data analysis, reporting  and interpretation - multivariate data analysis – OLS and logistic regression (logit/probit models), factor analysis (exploratory and confirmatory factor models), cluster analysis, reliability and validity tests;

Secondary data – use, availability, access and download secondary data;

An introduction to longitud inal data and longitudinal data analysis.

Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.