University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Statistics For Finance (CMSE11086)

Course Outline
SchoolBusiness School CollegeCollege of Humanities and Social Science
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryThis 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.


Data: Plots and Summaries
Introduction to Probability
Statistical Inference: Confidence Intervals, Hypothesis Tests, and p-values
The Simple Linear Regression Model
The Multiple Linear Regression Model

Student Learning Experience

The lectures will combine both theory and empirical examples. Additional examples will be solved at tutorials and extra exercises will also be available before the mid-term exam and the final exam. Students' real learning involves more than attending lectures. Students need to reflect on their learning and solve tutorial problems (in advance of tutorials) to learn best.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements For Business School PG students only, or by special permission of the School. Please contact the course secretary.
Course Delivery Information
Academic year 2018/19, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 14.5, Feedback/Feedforward Hours 1, Summative Assessment Hours 4, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 107 )
Assessment (Further Info) Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Additional Information (Assessment) Mid-term class test (multiple choice): 30%
Final exam: 65%
Class project: 5%
Feedback Students will get feedback in the tutorials. Marks for the mid-term class test will be provided to enable students to know how they are performing. The solutions for the mid-term will be discussed in a separate session. Students will also get general feedback on the final exam performance.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Statistics For Finance2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Define, explain and illustrate the concepts of probability, random variables, point estimation, interval estimation, hypothesis testing and inference.
  2. Critically discuss the link of theory with empirical applications.
  3. Understand and critically evaluate the importance of assumptions in statistics/econometrics.
  4. Carry out basic data analysis in STATA (students from the MSc in Banking and Risk Management will carry out regression analysis in SAS)
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.

Wooldridge, J. (2013), Introduction to Econometrics: Europe, Middle East and Africa Edition, Cengage Learning.

Although the main text of the course is Statistical Techniques in Business and Economics, Introductory Econometrics is an excellent reference for regression analysis and an invaluable text for carrying out econometric applications and writing down your dissertation. This is the main text for Research Methods (compulsory course for some master programmes in semester 2). Please note that both books by Wooldridge are pratically the same textbook but the European version is less expensive.

Resource List:
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.
Additional Class Delivery Information The course consists of ten two hour lectures plus weekly tutorials.
Course organiserDr Angelica Gonzalez
Tel: (0131 6)51 3027
Course secretaryMrs Kelly-Ann De Wet
Tel: (0131 6)50 8071
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information