Introduction to Quantitative Methods

Module title	Introduction to Quantitative Methods
Module code	INT3626
Academic year	2025/6
Credits	15
Module staff

Duration: Term	1	2	3
Duration: Weeks		10	10

Number students taking module (anticipated)	10

Module description

Many decisions in society are informed by an understanding of current trends and patterns. This is an increasingly important part of working life. This module introduces you to useful tools needed to search for, analyse and understand data.

You will learn the basics of statistical inference including probability; confidence intervals and how to identify patterns in data. You will also have an opportunity to apply statistical techniques to analyse and interpret real world data.

This module is essential for any student wishing to pursue a degree in data science or computer programming and will be of interest to any student intending to follow a decision-making career or further empirical study.

A reasonable numeracy level will be required before joining the module.

Module aims - intentions of the module

You will be introduced to standard procedures used in the collection and analysis of data. You will consider current research and the use made of data handling techniques in that research. You will carry out a very small-scale research project in their own area of interest and apply statistical techniques to analyse and interpret data. The module aims to introduce you to the skills needed to apply statistical techniques in the workplace or to undertake further study in this area.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. Demonstrate an understanding of data collection and sampling methods.
2. Demonstrate an ability to manipulate and summarise data.
3. Demonstrate an understanding of probability and statistical distributions, including their limitations.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

4. Accurately deploy established graphical methods of displaying data.
5. Critically evaluate a current piece of research.

ILO: Personal and key skills

On successfully completing the module you will be able to...

6. Communicate statistical information to specialist and non-specialist audiences.
7. Initiate and carry out a small project.
8. Demonstrate an ability to use quantitative methods in real life.

Syllabus plan

Types of data, sources of data
Data collection methods including bias, uncertainty and missing data.
Presenting data
Summarising data
Probability
Confidence intervals
Linear regression
Probability distributions: Normal distribution and Binomial distribution

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
40	110	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled Learning and Teaching Activities	40	Small group teaching
Guided Independent Study	110	Completing exercise sheets and studying research articles. Small project involving collection and interpretation of data.

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Fortnightly Exercise Sheets	1-2 hours each	1, 2, 3, 4, 8	Verbally in class or written feedback on script.
In class tests	30 mins to 1 hour each x 5	1,2,3,4,5,6	Verbally in class or written feedback on script.
Report commenting on a piece of current research	400 words	5, 6	Discussion with Peers
Small scale individual report	800 words	1,2,3,4,7,8	Peer review and written and verbal feedback

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
100	0	0

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Presentation: evaluation of piece of current research	50	10 minutes per person + 5 minutes question/answer	5, 6	Peer review and verbal feedback on presentation
Individual Quantitative Project report	50	2000 words including tables and diagrams	1, 2, 3, 4, 7, 8	Written feedback on formal application

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Presentation	Presentation (deferral) (see details of summative assessment)	5,6	ASAP and before Pre-APAC
Individual Quantitative Project report	Report (deferral) (see details of summative assessment)	1, 2, 3, 4, 7, 8	ASAP and before Pre-APAC
n/a	Referral viva	all	ASAP and before Pre-APAC
			ASAP and before Pre-APAC

Re-assessment notes

Deferral –if you miss an assessment for reasons judged legitimate by the Mitigation Committee, the applicable assessment will normally be deferred. See ‘Details of re-assessment’ for the form that assessment usually takes. When deferral occurs there is ordinarily no change to the overall weighting of that assessment.

Referral –if you have failed the module overall (i.e. a final overall mark of less than 40% achieved) you will be required to attend a Viva to discuss the research in your individual report. Only your performance in this viva will count towards your final module grade. A grade of 40% will be awarded if the examination is passed. Referral assessments will assess all ILOs (i.e. skills and knowledge) assessed on the module. A grade of 40% will be awarded if the viva is passed.

Indicative learning resources - Basic reading

Basic reading:

Rowntree D. (2004) Statistics without Tears. ISBN: 9780205395095

Indicative learning resources - Web based and electronic resources

Web-based and electronic resources:

ELE – College to provide hyperlink to appropriate pages

Key words search

Data sampling, Probability, Data collection, Linear regression, Data Science

Credit value	15
Module ECTS	7.5
Module pre-requisites	None
Module co-requisites	None
NQF level (module)	6
Available as distance learning?	No
Origin date	01/05/2022
Last revision date	10/06/2025