Postgraduate Course: Statistics For Finance (CMSE11086)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | This course will provide you with the statistical concepts needed for financial applications. The goal is to apply statistical tools to analyse data, solve problems and make business decisions. This introductory course will provide you with the essential background for subsequent courses. |
| Course description |
The content of this course is similar to an advanced undergraduates statistics course. Although there is a strong emphasis on theory, you will get an introduction to an econometric software for conducting basic empirical research. The material is presented to understand, rather than memorise, statistical concepts. The course shall be accessible for both, students with strong quantitative background, and those who are ready to put effort into the class material.
Syllabus:
Data: Plots and Summaries
Introduction to Probability
Probability
Statistical Inference: Confidence Intervals, Hypothesis Tests, and p-values
The Simple Linear Regression Model
The Multiple Linear Regression Model
Student Learning Experience:
Tutorial/seminar hours represent the minimum total live hours - online or in-person - a student can expect to receive on this course. These hours may be delivered in tutorial/seminar, lecture, workshop or other interactive whole class or small group format. These live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | For Business School PG students only, or by special permission of the School. Please contact the course secretary. |
Information for Visiting Students
| Pre-requisites | Business School postgraduate students only. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2021/22, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Seminar/Tutorial Hours 15,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
132 )
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| Additional Information (Learning and Teaching) |
Seminar/Tutorial hrs are the min total live hrs, online or in-person, students can expect to receive
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% coursework (individual) - assesses all course Learning Outcomes |
| Feedback |
Formative feedback:
Students are strongly encouraged to ask questions and participate in group discussions. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Define, explain and illustrate the concepts of probability, random variables, point estimation, interval estimation, hypothesis testing and inference.
- Critically discuss the link of theory with empirical applications.
- Understand and critically evaluate the importance of assumptions in statistics/econometrics.
- Carry out basic data analysis in a statistical software package.
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Reading List
Douglas A. Lind, William G Marchal, Samuel A. Wathen (2012), Statistical Techniques in Business and Economics, 15th Edition, McGraw-Hill
Wooldridge, J. (2015), Introductory Econometrics: A Modern Approach, 6th edition, Thomson.
Resource List: https://eu01.alma.exlibrisgroup.com/leganto/public/44UOE_INST/lists/26181354100002466?auth=SAML |
Additional Information
| Graduate Attributes and Skills |
Cognitive Skills:
The course will develop analytical, numerical and problem-solving skills.
Subject Specific Skills:
Students will gain an ability to understand and use statistics notation and theory to solve a wide range of problems in Finance.
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| Keywords | finStatisticsforFinance |
Contacts
| Course organiser | Dr Angelica Gonzalez
Tel: (0131 6)51 3027
Email: angelica.gonzalez@ed.ac.uk |
Course secretary | Mrs Kelly-Ann De Wet
Tel: (0131 6)50 8071
Email: K.deWet@ed.ac.uk |
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