Applied Statistics for Finance and Economics (L1064)
15 credits, Level 5
Spring teaching
On this module, you'll be introduced to the empirical use of various statistical methods commonly used in the social sciences. You'll learn about best statistical practices through the exploration and analysis of real-world data.
Topics covered include:
- measuring skewness and kurtosis in empirical data
- undertaking tests for normality, goodness-of-fit, and non-parametric testing principles
- ANOVA and experimental design
- OLS and maximum likelihood estimation in the bivariate regression model
- the linear probability and logistic models
- detrending, deseasonalising, and forecasting using time series data
- basic concepts in sample survey methods.
Teaching
52%: Lecture
22%: Practical (Workshop)
26%: Seminar
Assessment
50%: Coursework (Report)
50%: Examination (Unseen examination)
Contact hours and workload
This module is approximately 150 hours of work. This breaks down into about 32 hours of contact time and about 118 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.
We’ll make sure to let you know of any material changes to modules at the earliest opportunity.