FINN1037: Quantitative Methods 2

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• 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.

• Introduction to probability and uncertainty.
• Probability Density Functions and Probability Mass Functions.
• Descriptive statistics
• Bayesian Statistics
• Fitting probability functions and the method of maximum likelihood.
• Hypothesis testing and the NeymanPearson/Frequentist approach.
• Linear regression models and the least squares estimator.

Subject-specific Knowledge:

• 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 difference in the intuition between Bayesian and Frequentist analysis and critically evaluate evidence from statistical techniques applying these approaches.

Subject-specific Skills:

• 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.

Key Skills:

• 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.

• 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 multiple-choice timed test in term and an assignment.

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