What will I learn on this module?
This module provides you with the knowledge and skills of applying a variety of practical mathematical and statistical methods that are used to analyze and interpret financial data. On the side of mathematics, you will be introduced to a range of subject specific formulas, and related operations such as factoring, grouping, and transposition. This will be used as an opportunity to review key notation and basic mathematical operations. Subsequently, linear and some important non-linear functions will be examined in the context of main theories from economics and finance. In particular, supply and demand theory and the time value of money concepts will be used as key contexts in the example of how important formulas are derived. On the side of statistics, you will be exposed to formal descriptive statistics and introduced to the key probability distribution functions such as Binomial, Poisson and Normal. You will use the named probability distribution functions to learn how to formally formulate hypotheses.
How will I learn on this module?
You will be taught formal content in lectures where presentation slides will contain detailed descriptions of notation, formulas, rules, properties and operations with respect to key derivations. Lectures will also be used to introduce both financial and economic theories relevant to this module. Each lecture will be supported by a seminar in a computer lab where the corresponding mathematical or statistical task will be solved both on the board (manually) and in Excel. Every formula which is used in this module will be formally derived to expose the intuition and prepare students for thorough and formal interpretation of results. In this respect the seminar tasks will be designed not to test operational capabilities of Excel, but to strengthen understanding of how a particular calculation is performed and more importantly its subject related meaning and limitations.
This module will be assessed by an open notes exam with both a hand written and EXCEL based components.
How will I be supported academically on this module?
The academics in the teaching team taking both the lectures and seminars will provide input and support. This module relies a great deal on internet resources. Content directly related to the module will be posted to Northumbria e-learning portal, and all lectures will be recorded on Panopto. Electronic reading list will used as a guide for weekly reading material which will also rely on content drawn from free on line sources such as Khan Academy (https://www.khanacademy.org/) and for more advanced topics MIT open course ware (https://ocw.mit.edu/index.htm).
What will I be expected to read on this module?
All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)
What will I be expected to achieve?
Knowledge & Understanding:
Understand and apply a variety of mathematical and statistical techniques and their application to the analysis and interpretation of financial problems (MLO1).
Intellectual / Professional skills & abilities:
Evidence skills in describing financial and economic data in preparation for more advanced modelling (MLO3).
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
Understand and apply the role of mathematical techniques as an aid to decision making; through the selection of specific tools and techniques to assist in the solution of financial problems (MLO2)
How will I be assessed?
Formative Assessment
This module will have ongoing tests on the main topics detailed in the teaching and learning plan throughout the semester and feedback will be provided on an individual and class basis within the workshops.
Summative Assessment
This module will be assessed by a two-hour open notes exam with ten minutes reading time.
(MLO1, MLO2 and MLO3)
Pre-requisite(s)
None
Co-requisite(s)
None
Module abstract
The disciplines of mathematics and statistics offer a wide range of powerful tools, which are indispensable to the study of economics, accounting and finance. While studying on this module you will be introduced to parts of mathematics and statistics which are most prominently featured in key models and formulas. You will learn the intuition behind mathematical derivations of some of these formulas revealing their origin and meaning. Equally, we will cover basic descriptive statistics which is the first step in the analysis of ever increasing data sets. Through this you will advance your awareness and understanding of mathematical and statistical underpinnings behind financial and economics theories that you will study on the corresponding programs.
Course info
UCAS Code N775
Credits 20
Level of Study Undergraduate
Mode of Study 1 year full-time followed by a further 3 years full-time study or 4 years with a placement (sandwich)/study abroad
Department Newcastle Business School
Location City Campus, Northumbria University
City Newcastle
Start September 2024 or September 2025
All information is accurate at the time of sharing.
Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.
Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.
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