Module FINN1037: Quantitative Methods 2

Department: Finance

FINN1037: Quantitative Methods 2

Tied To

• Finance: (programme not found)
• Finance with Placement Year: (programme not found)
• Finance with Study Abroad: (programme not found)
• N305: Finance
• N306: Finance with Placement Year
• N307: Finance with Study Abroad

Pre-requisites

Corequisites

Excluded Combinations

Aims

• To introduce students to the essential analytical and statistical techniques necessary in their degrees, to support other year 1 modules and to provide a foundation for further study.

Content

• Introduction to statistics, data fundamentals, organisation and visualisation
• Measures of central tendency and dispersion
• Basic probability concepts and distributions
• Sampling and the Central Limit Theorem
• Confidence intervals and sample size determination
• Hypothesis testing in finance
• Introduction to regression analysis and its applications in finance

Learning Outcomes

• By the end of the module students should:
• Have knowledge of the foundational statistical techniques that underpin those studied in further core and optional modules on the degree.
• Understand that statistical techniques are underpinned by assumptions and be able to design statistical experiments using data.
• Have knowledge of the variety of use cases for different statistical techniques and be confident to adapt and apply them in a number of contexts.
• Have sufficient knowledge to critically evaluate statements made regarding data and understand confidence, significance and statistical power.
• Understand the principles of regression analysis and its potential applications in modelling and predicting financial relationships

• Will have acquired an array of mathematical and statistical skills widely used in finance and business.
• Be prepared for successful study of second year core modules in finance, economics and business.

• Written communication - through formative and summative assessment.
• Adaptive problem solving and critical thinking when applying statistical techniques to data and the ability to critically evaluate statistical evidence.
• Be able to learn new techniques based on those studies in this module.
• Have appropriate skills in designing statistical experiments using data.
• Computer literacy through the use of appropriate statistical software.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Workshops will deliver essential material in an efficient way to a large audience and will identify key reading and exercises.
• Students are arranged in subgroups in each workshop and the classes are divided into a whole class and subgroup component.
• Formative assessment is by means of exercises undertaken in the workshops.
• Summative assessment is by means of a written in-person exam and an assignment. 

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment

A range of exercises will be completed throughout the module in workshops.