Postgraduate Course: Statistics for Analytics (CMSE11624)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course introduces students to principles of business statistics and aspects of decision-making needed for banking and risk analytics. It examines aspects of decision making in business and banking with regards to fundamentals of statistical analysis. |
| Course description |
The aim of the course is to help students develop an understanding of the core statistical techniques and data ethics in business. A particular emphasis is placed on developing the ability to interpret the numerical information that forms the basis of decision-making in business. Most of the examples are drawn from a variety of business, banking, and risk management applications.
This course introduces core business statistics and fundamental aspects of decision-making. It examines aspects of business and banking with regards to principles of statistical analysis. Students will be provided with the theoretical concepts, tools and methods of statistics as well as the opportunity to work through example problems.
Outline Content
- Data, data collection, and data ethics
- Descriptive and summary statistics
- Probability and probability distribution
- Sampling and sampling distribution
- Point estimation and confidence interval
- Hypothesis formulation and testing
- Correlation and independence
- Simple linear regression
- Multiple linear regression
Student Learning Experience
Students will have to read the textbooks stated below in the Required Texts section. Weekly lectures will explore the key concepts of business statistics. During lectures students will be asked to be active, and to raise any issues that present difficulties. Example problems will be distributed after the lecture.
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Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 18,
Seminar/Tutorial Hours 4,
Dissertation/Project Supervision Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
172 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
50% Coursework (individual) - Assesses course learning outcomes 1,2,4,5
50% Coursework (group) inlcudes 20% peer review - Assesses course learning outcomes 1,3,4 |
| Feedback |
Formative: Feedback will be provided throughout the course.
Summative: Feedback will be provided on assessments within agreed deadlines. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Critically understand and discuss the key terminology, principles, concepts tools and techniques used in business statistical analysis.
- Critically evaluate the underlying assumptions of analysis tools.
- Understand and critically discuss the issues surrounding sampling and significance.
- Discuss critically the uses and limitations of statistical analysis and communicate effectively with peers.
- Solve a range of business decision-making problems using the techniques covered.
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Learning Resources
Anderson/Sweeney/Williams/Camm/Cochran/Freeman/Shoesmith. Statistics for Business and Economics. Cengage Learning; 2020.
Michael Barrow. Statistics for Economics, Accounting and Business Studies. Sixth edition.. Pearson; 2013.
Bandyopadhyay, Arindam. Basic Statistics for Risk Management in Banks and Financial Institutions. Oxford University Press, 2022.
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Additional Information
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills
After completing this course, students should be able to:
-Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.
Knowledge and Understanding
After completing this course, students should be able to:
-Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.
-Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore and solve them responsibly.
Cognitive Skills
After completing this course, students should be able to:
-Be self-motivated; curious; show initiative; set, achieve and surpass goals; as well as demonstrating adaptability, capable of handling complexity and ambiguity, with a willingness to learn; as well as being able to demonstrate the use digital and other tools to carry out tasks effectively, productively, and with attention to quality. |
| Keywords | Statistics,Probability,Hypothesis test,Regression,Data Ethics |
Contacts
| Course organiser | Dr Zexun Chen
Tel: (0131 6)50 8074
Email: Zexun.Chen@ed.ac.uk |
Course secretary | Miss Aoife McDonald
Tel: (0131 6)50 8074
Email: Aoife.McDonald@ed.ac.uk |
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