QUANTITATIVE METHODS - 2023/4
Module code: ECO1015
This module ensures that every student acquires the basic mathematical and statistical skills necessary for their subsequent modules, irrespective of their prior education. Students will learn to solve mathematical optimisation problems, which lie at the heart of every economic model. This module will provide students with techniques for maximising real-valued functions with one variable; functions with several variables will be covered in subsequent modules. Economic applications of the mathematical techniques are emphasised throughout.
LAOHAKUNAKORN Krittanai (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 4
JACs code: G100
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 85
Lecture Hours: 22
Tutorial Hours: 5
Guided Learning: 38
Prerequisites / Co-requisites
Indicative content includes:
- Numbers, sets, logic
- Mathematical functions of one variable, including linear, quadratic, logarithmic, and exponential functions
- Properties of functions: monotonicity, concavity/convexity, inverse functions
- Sequences and limits, differentiation
- Methods for solving optimisation problems
- Probability, conditional probability, Bayes’ rule
- Random variables, probability distributions, including binomial, Poisson, and normal
- Economic applications
|Assessment type||Unit of assessment||Weighting|
|Online Scheduled Summative Class Test||Online Test 1 within a 4hr window||15|
|Online Scheduled Summative Class Test||Online Test 2 within a 4hr window||25|
|Examination||EXAMINATION (120 MIN)||60|
The assessment strategy is designed to provide students with the opportunity to demonstrate their understanding of the mathematical and statistical concepts and their ability to apply this knowledge to economic problems.
Thus, the summative assessment for this module consists of:
- Two class tests and a final exam.
Sample questions and solutions for each assessment are available.
Formative assessment and feedback
Review questions and self-tests designed to check the students’ understanding of the lecture material are provided every week. There are also biweekly tutorials: for these, students are provided with a set of exercises to solve before the session, and in the tutorial they receive guidance and feedback on their answers. Students are encouraged to ask for feedback during office hours, via email, or via the SurreyLearn discussion forum.
- Highlight the role and importance of mathematical models in economics.
- Introduce students to a mathematical way of thinking.
- Help students develop their ability to solve mathematical problems.
- Illustrate the usefulness of mathematical methods with economic applications.
- Ensure that each student acquires the quantitative skills necessary to succeed in subsequent modules.
|001||Students will be able to understand the meaning and interpretation of mathematical models||KCT|
|002||Students will become aware of the advantages and disadvantages of mathematical modelling in economics||KCT|
|003||Students will be able to formulate and solve mathematical optimisation problems that provide insights into economic phenomena||KCPT|
|004||Students will be able to use probability theory to solve problems that involve uncertain outcomes||KCPT|
|005||Students will be able to apply mathematics and statistics to real world problems||KCPT|
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:
Provide students with a broad set of tools and techniques to understand and solve mathematical problems
Provide students with the essential background in probability and statistics.
Lectures provide students with the theory required to solve a wide range of economic problems with mathematical tools. Students engage with the module material by solving a large number of practice problems each week, and are encouraged to raise any difficulties they encounter with the module leader. The emphasis on solving practice problems reflects a belief that the best way to learn maths is by doing maths. Tutorials are a further opportunity for students to receive guidance and feedback on their work.
The learning and teaching methods include:
- 2 hour lecture per week x 11 weeks
- 1 hour tutorials x 5 weeks
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.
Upon accessing the reading list, please search for the module using the module code: ECO1015
The School of Economics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities particularly in the following areas:
Students will develop the ability to think analytically and learn to solve a wide range of mathematical problems, including those that they are likely to face at interviews/assessment days.
Programmes this module appears in
|Economics and Finance BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Business Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Politics and Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
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 2023/4 academic year.