Postgraduate Course: Business Statistics (CMSE11206)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | This course introduces students to principles of business statistics and aspects of decision-making. It examines aspects of business and marketing with regards to fundamentals of statistical analysis. |
| Course description |
The aim of the course is to help you develop an understanding of the core quantitative techniques from statistics. 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 applications.
This course introduces core business statistics and fundamental aspects of decision-making. It examines aspects of business and marketing 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.
Syllabus
Exploratory and descriptive statistics
Probability, probability distributions
Continuous probability distributions, sampling and sampling distributions
Statistical inference and estimation
Introduction to hypothesis testing
Further hypothesis tests and tests of independence
Non-parametric methods
Correlation and regression
Introduction to Multivariate analysis
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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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2017/18, 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
(
Lecture Hours 20,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
125 )
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| Additional Information (Learning and Teaching) |
Working on examples 40 hrs; prep reading 10 hrs; prep for summative assessment 75 hrs.
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| Assessment (Further Info) |
Written Exam
70 %,
Coursework
30 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Exam (weighted 70%)
Assignment (weighted 30%).
The assignment is due by 2pm on Tuesday 22nd November (Week 10).
The assignment topic and details will be distributed by Monday of Week 9.
The degree examination will take place during the December exam diet, which runs from 8th to 21st December 2016 (with the exact date to be determined by the University during the first Semester). |
| Feedback |
Assessment feedback will be provided on a feedback form in the appropriate format. Assessment marks and feedback will be comprise discussion of solutions to example problems on material, feedback on assignment and generic feedback on exam. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S1 (December) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Describe and discuss the key terminology, 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.
- Solve a range of problems using the techniques covered.
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Reading List
Core text:
Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E. (2010) Statistics for Business and Economics, South-Western Cengage Learning. (also 2009, 2011, 2014 International or European editions).
Recommended:
- Barrow, M., (2009) Statistics for Economics, Accounting and Business Studies (5th ed.) Pearson Education (e-resource is available at the library).
- Malhotra, N. & Birks, D. Marketing Research: An Applied Approach / FT Prentice Hall, 2006 or 2000.
Advanced reading (beyond the scope of the course):
- Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2014) Multivariate data analysis..Harlow, Essex : Pearson
- Tabachnick, B.G. , Fidell, L.S. (2014) Using multivariate statistics. Harlow, Essex: Pearson.
For all books earlier or later editions are suitable; all books are in the UoE library. |
Additional Information
| Graduate Attributes and Skills |
Cognitive Skills:
After completing this course, students should be able to:
- understand key concepts of statistics;
- recognise statistical techniques appropriate to the analysis of particular business problems or situations;
- select appropriate statistical techniques and evaluate their advantages and disadvantages;
- calculate and interpret business statistics.
Subject Specific Skills:
After completing this course, students should be able to:
- identify relevant quantitative techniques which are best suited to solve a particular management problem or answer a particular research question;
- use a variety of quantitative techniques in different business applications;
- interpret the results of the quantitative analysis and communicate these results in a clear and coherent way;
- use their experience of data analysis and of applying business statistics techniques;
- access and interpret existing business statistics information. |
| Keywords | Mark-BS |
Contacts
| Course organiser | Dr Galina Andreeva
Tel: (0131 6)51 3293
Email: |
Course secretary | Miss Ashley Harper
Tel: (0131 6)51 5671
Email: |
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