IF0QFE: Quantitative Methods for Finance and Economics

Module code: IF0QFE

Module provider: Global Academy

Credits: 20

ECTS credits: 10

Level: F

When you’ll be taught: Semester 2

Module convenor: Miss Natalie Drake, email: n.drake@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE IF0MFE (Compulsory)

Pre-requisite or Co-requisite module(s):

Module(s) excluded: IN TAKING THIS MODULE YOU CANNOT TAKE IF0QMS OR TAKE IF0QFEJ (Compulsory)

Placement information: NA

Academic year: 2026/7

Available to visiting students: No

Talis reading list: Yes

Last updated: 26 March 2026

Overview

Module aims and purpose

This module introduces the key elements of statistics to an A-level standard. The module develops core quantitative techniques that prepare students for more advanced study in undergraduate degree programmes in finance and economics. Through learning how to analyse and solve a range of statistical problems, students develop both theoretical understanding and practical numerical skills, including those relevant to their intended degree pathways. This foundation enables students to approach quantitative analysis and data-driven decision-making in their undergraduate studies with confidence. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. apply statistical calculation and interpretation skills using real-world financial and economic contexts 
2. represent situations mathematically and graphically to understand relationships between contextual problems and their solutions 
3. analyse financial data, recognise normal and binomial distributions, and calculate associated probabilities 
4. use the language of hypothesis testing and interpret statistical findings. 

Module content

This module begins with a range of basic techniques including presenting and summarising data, descriptive statistics such as measures of central tendency and dispersion. This is followed by probability theory, correlation, regression and time series.   

In the second half of the semester, binomial and normal distributions are covered alongside hypothesis testing. 

Students will cover this content by hand and using Excel. 

Structure

Teaching and learning methods

The delivery pattern of this module will be one lecture, one seminar, and one practical each week.

Feedback and feedforward are provided through face-to-face sessions for students in person and posted on Blackboard for summative assessments. Students will also be expected to take responsibility for their own learning by setting goals and making regular use of the University library, especially their online resources for students working remotely, Blackboard (the University Virtual Learning Environment) and other online resources.

For students studying at our campus in Malaysia: This module may be taught in a different semester and the breakdown of study hours may differ to those set out in the Study Hours table (please refer to the Module Handbook for the correct breakdown). In addition, you will be required to complete an additional 40 hours of study, taking the total number of study hours to 240 for this module. This is to comply with the Malaysian Qualifications Agency (MQA). 

Study hours

At least 66 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module. 

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or a DAS-agreed extension as a reasonable adjustment indicated in your Individual Learning Plan): 10% of the total marks available for that piece of work will be deducted from the mark for each calendar day (or part thereof) following the deadline up to a total of three calendar days;
• where the piece of work is submitted up to three calendar days after the original deadline (or a DAS-agreed extension as a reasonable adjustment indicated in you Individual Learning Plan), the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three calendar days after the original deadline (or a DAS-agreed extension as a reasonable adjustment indicated in your Individual Learning Plan), no penalty shall be imposed;
• where the piece of work is submitted more than three calendar days after the original deadline (or a DAS-agreed extension as a reasonable adjustment indicated in your Individual Learning Plan): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three calendar days of the deadline (or a DAS-agreed extension as a reasonable adjustment indicated in your Individual Learning Plan): no penalty will be applied;
• where the piece of work is submitted more than three calendar days after the original deadline (or a DAS-agreed extension as a reasonable adjustment indicated in your Individual Learning Plan): a grade of Fail will be awarded.

Where a piece of work is submitted late after a deadline which has been revised owing to an extension granted through the Assessment Adjustments policy and process (self-certified or otherwise), it will be subject to the maximum penalty (i.e., considered to be more than three calendar days late). This will also apply when such an extension is used in conjunction with a DAS-agreed extension as a reasonable adjustment.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Regular tutorial classes on problems of the type encountered in examinations. Additional exercises based on lectures (students send in solutions to gain feedback, with some automated marking being used).  Optional drop-in sessions.

All summative pieces are given formative feedback to enhance their effectiveness.

A mock will be provided before each exam, and weekly feedback will be given for coursework

Reassessment

Additional costs