Mid-term exam

1 - Written exam - 50

Final exam 

2 - Written exam - 50

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<ol><li>Introduction to algebra and functions.</li><li>Calculus for Finance</li><li>Partial derivatives and constrained optimisation</li><li>Financial Mathematics</li><li>Descriptive Statistics and data visualisation</li><li>Probability theory and distributions</li><li>Hypothesis testing and confidence intervals</li><li>Simple and multiple regression analysis</li><li>Time series analysis</li></ol>

Feedback is provided in a number of ways throughout your module. This includes feedback you receive during teaching from both peers and lecturers and that provided for formative assessment. Following an assessment, you will be given your marks and feedback in line with the assessment regulations and policy. More information on the timing and type of feedback that will be provided for each assessment will be available from the module leader. <a href='https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations'>https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations</a>

This module will support the development of all the graduate attributes. Your module leader will provide you with information about how your learning, teaching and assessment activities support your development of these attributes. The graduate attributes are: - Always learning - Engaged in the world - Technical and digital - Connected Professional - Creating Impact

In-Person - 

Self-directed - 

Statistics for Business and Economics

Introductory Econometrics: A Modern Approach

Mathematics for Economics and Business

Calculus for Business and Economics, An Example-Based Introduction

Introductory Econometrics for Finance

IS4002 - Advanced Mathematics and Quantitative Methods 

IS4002-PRD2-PER-OC

A variety of learning and teaching methods will be used in this course.
During the lectures, key themes, theories and concepts are introduced using a combination of visual aids, discussions, demonstration questions and interactive activities. You are encouraged to actively participate during the lectures and to take your own notes.  Seminars include problem-solving questions, analysis of case studies, group discussions and interactive activities. Classroom activities are designed to enhance student knowledge and ability to apply the learnt concepts.
Lectures and seminars will be delivered based on the principles of Content and Language Integrated Learning (CLIL) to support your experience of learning in a second language, and to develop your competence in using subject-specific language at high academic levels.  
Key learning and teaching resources will be put on the module page on the Virtual Leaning Environment. Materials are available before each session to enable you to prepare better for these sessions.
In addition to the hours devoted to lectures and seminars, you are expected to dedicate additional time, outside of formal contact teaching hours, to independent learning, both directed as well as self-directed:
Directed learning refers to learning which is guided by your teachers. Each week, your teachers will provide you with directed-learning tasks which you are expected to complete outside of contact hours. This might take a variety of formats. For instance, these could be recorded lectures accompanied by online quizzes. Directed learning tasks could be pre- or post-lesson tasks. The former prepares you for upcoming lectures or seminars; the latter reinforces content covered in previous lectures or seminars.  Completing directed learning tasks on time will enable you to maximise your learning from lectures and seminars. Instructions for your weekly directed learning tasks can be found on our Virtual Learning Environment.
Self-directed learning refers to learning which is not assigned to you by your teachers but which you undertake on your own. This might take the form of reading lecture slides in advance of lectures; reviewing lesson material after lessons; completing additional exercises or recommended readings or preparing for your assessments. Self-directed learning involves reflecting on your learning, identifying your learning needs and creating a study plan.
You will also be assigned a Personal Tutor who will guide you through your programme and support you in your personal, academic and professional development.  You are expected to attend Personal Tutorial sessions, either individually or as a group. These sessions help monitor your well-being and academic progress and are an opportunity to discuss academic and non-academic matters. 
Your performance on this programme will be monitored regularly and you will receive two academic reports during the year to inform you of your academic progress.

Advanced Mathematics and Quantitative Methods 

Use autoregressive and moving average models for time series data.

Skills

Adopt an analytic approach to problem solving.

Values and attitudes

Develop the ability to use your own judgement when interpreting results.

Solve simple investment problems involving annuities.

Demonstrate understanding of different measures of location and dispersion

Knowledge

Demonstrate knowledge of key algebraic techniques and function behaviour.

Show how calculus is used to model economic and financial processes.

Apply the mathematical concepts used in financial mathematics.

Apply the concepts of probability theory.

Understand the concepts of linear and multiple regression.

Develop problem solving skills, including developing an appropriate mathematical model.

Analyse quantitative data and calculate key indicators.

Use a variety of analytical and quantitative tools to support decision-making in finance.

Use appropriate probability distributions according to the context.

Develop linear and multiple regression models.

Use spreadsheets and other statistical software packages such as SPSS, and interpret their output.

Recognise the usefulness and limitations of mathematical models.