ECO-20049 - Statistics with Bloomberg
Coordinator: Panos Sousounis Tel: +44 1782 7 33623
Lecture Time: See Timetable...
Level: Level 5
Credits: 15
Study Hours: 150
School Office: 01782 733094

Programme/Approved Electives for 2022/23

None

Available as a Free Standing Elective

Yes

Co-requisites

None

Prerequisites

ECO-10027 Quantitative Methods II

Barred Combinations

None

Description for 2022/23

This module is designed to introduce students to key concepts of statistics; and to illustrate them using the School's Bloomberg terminals, thus also enabling familiarity with the Bloomberg portal of information.
The module will deliver the theoretical material in standard lectures, but it will adopt a clear hands-on approach in classes that will be held in the Bloomberg computer laboratory. In these classes, students will have the opportunity to become familiar with Bloomberg, derive economic and/or business and/or financial information from this portal, and apply their knowledge of statistics in relation to this information. The students will also prepare for their portfolio piece of coursework during these lab-based classes.

Aims
To revise key concepts of statistics introduced in ECO-10027, and to illustrate their practical applications using the Bloomberg Terminal, thus also enabling familiarity with the Bloomberg portal of information.

Talis Aspire Reading List
Any reading lists will be provided by the start of the course.
http://lists.lib.keele.ac.uk/modules/eco-20049/lists

Intended Learning Outcomes

demonstrate understanding of key concepts of statistics, including the mean, variance, distribution and hypothesis testing: 1
formulate problems and hypotheses in a statistical framework, and choose the appropriate tests to address them: 1
apply the chosen statistical models and methods, evaluate the evidence and interpret the results of the statistical analysis: 1
demonstrate the ability to use the Bloomberg information portal: 1

Study hours

16 hours lectures
8 hours tutorial computer lab classes
30 hours portfolio preparation
96 hours self study which includes practice of the skills taught on the module, reading of additional materials, thinking time and discussion of topics with other students.



School Rules

None

Description of Module Assessment

1: Portfolio weighted 100%
Portfolio of practical exercises
Students are asked to submit a portfolio of 8 out of 8 practical exercises discussed during the module. One practical exercise will be discussed in each of the 8 seminars. The portfolio should be submitted at the start (Tuesday) of teaching week 12.