Course co-ordinator(s): Dr Mateusz Majka (Edinburgh).
Aims:
To provide students with: an introduction to the use of descriptive statistics in economics and financial contexts; a range of quantitative methods that have immediate application in economics and financial settings; the use of Excel as a tool in the problem solving process; and the development of statistical problem solving skills.
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisites: none.
Location: ALP, Dubai, Edinburgh, Malaysia.
Semester: 1.
Syllabus:
The nature of statistics; frequency distributions and graphical analysis; measures of central tendency and dispersion;
probability; discrete and continuous probability distributions; models for count data and measurement; the central limit
theorem; confidence intervals with samples from one or two populations; hypothesis testing including test statistics for
typical situations involving one or two samples; association between two variables; correlation, contingency tables and chisquare test for association; index numbers; linear programming.
Learning Outcomes: Subject Mastery
- Understanding the nature of statistics and their value in economics and finance.
- Ability to describe the characteristics of data, including the differences in nature between qualitative and
quantitative data - Understanding of the nature of a probability distribution and the characteristics of data generated by different
types of process - Construct, calculate and interpret confidence intervals for parameters of interest in one or two population
- Understanding and interpreting the concepts of null hypothesis, alternative hypothesis and critical region
- Perform hypothesis tests for situations involving one or two samples
- Perform chi-squared goodness-of-fit tests in appropriate situations
Learning Outcomes: Personal Abilities
- Awareness of the scope of quantitative analysis in economics and finance
- Understanding of the nature of professional practice relating to the analysis and use of quantitative and qualitative data in accountancy and finance
Assessment Methods: Due to covid, assessment methods for Academic Year 2021-22 may vary from those noted on the official course descriptor. Please see the Computer Science Course Weightings and the Maths Course Weightings for 2020-21 Semester 1 assessment methods.
SCQF Level: 8.
Credits: 15.
Other Information
Help: If you have any problems or questions regarding the course, you are encouraged to contact the lecturer
Canvas: further information and course materials are available on Canvas