Programme/Approved Electives for 2019/20
Available as a Free Standing Elective
This module is designed especially to cater for the needs of students taking the Single Honous Principal Economics, Business Economics, Principal Finance, or Accounting and Finance. The module is structured to assist them in understanding the technical and quantitative aspects of the subject. The module will introduce and develop students' understanding of econometrics and the use of statistical methods to investigate selected economic and financial issues (e.g. consumption functions, household labour supply, CAPM) in order to facilitate the reading of published empirical articles in their other modules.
The aim of this module is to demonstrate the application of theoretical and empirical quantitative methods to particular issues in economics and finance. The unit describes how to formulate an economic model, estimate the model, interpret and evaluate the results. Students will learn these concepts through practical classes, which will lead them to develop investigative/research skills.
Intended Learning Outcomes
Apply the elements of statistical inference in a variety of different contexts: 1,2,3Evaluate the adequacy of a given model using a battery of diagnostic tests: 1,2,3Formulate data analysis problems in a statistical framework, choose appropriate models for situations involving uncertainty, and understand their key elements and properties: 1,2,3Apply statistical models and methods to solve practical problems; evaluate statistical evidence; interpret the results of statistical analyses; comment critically on econometric modelling approaches.: 1,2,3Use industry standard software for statistical analysis: 1,2,3Use the methodologies for data analysis, such as: analysis of variance and simple and multiple regression: 1,2,3
24 hours lectures10 hours tutorials/lab classes20 hours preparation for classes20 hours assignment preparation76 hours independent study
ECO-20049 Statistics with Bloomberg
1: Portfolio weighted 20%
Description of Module Assessment
Portfolio consisting of 4 online exercises set during the semester.Exercises will be marked when submitted at different points during the semester. Best 3 marks will contribute to overall assessment.2: Exam weighted 60%
Two-hour end of semester unseen examinationTwo-hour, closed book examination3: Report weighted 20%
Short report based on lab class exercise800-word report on STAT output analysing a data set used during the computer lab classes.