Postgraduate Course: Business Statistics (MBA) (BUST11210)
Course Outline
| School |
Business School |
College |
College of Humanities and Social Science |
| Course type |
Standard |
Availability |
Not available to visiting students |
| Credit level (Normal year taken) |
SCQF Level 11 (Postgraduate) |
Credits |
10 |
| Home subject area |
Business Studies |
Other subject area |
None |
| Course website |
None
|
Taught in Gaelic? |
No |
| Course description |
This course covers a relatively broad range of the statistical concepts and techniques applied to management disciplines. Statistical analysis deals with the consideration of orders of magnitude, relationships, and differences. Two categories of analysis characterize such endeavour. Descriptive Statistics will summarize data in terms of key measurements that capture the data's essential features. Inferential Statistics considers the reliability of magnitudes, relationships, and differences discerned from sample data. Such discernment in turn depends on an appreciation of how very untypical samples are very improbable to the extent that resort has been made to a large amount of randomly selected data. Consideration of the logic of probability is therefore essential for an appreciation of the reliability of analysis based upon sample data.
The topics covered in the course tend to build on material covered in previous topics. Accordingly, efficient learning of course material will depend critically on its gradual assimilation, particularly by the timely completion of homework assignments. Problems with course material in general and homework assignments in particular should be alleviated by the availability of remedial tutorials for those who require them.
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
None
|
| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2011/12 Semester 1, Not available to visiting students (SS1)
|
WebCT enabled: Yes |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| No Classes have been defined for this Course |
| First Class |
First class information not currently available |
| No Exam Information |
Summary of Intended Learning Outcomes
Knowledge and Understanding:
On completion of this course students should:
a) Appreciate a broad range of powerful but simple statistical applications that can be used to conduct research in all management disciplines.
b) Understand the power of analysis based on random sampling and the role of sample size in reducing error in such sampling.
c) Understand the particular meaning statisticians assign to commonly used terms such as random, significant, biased, correlated, and estimated. Such terms should be used with care in empirical analysis.
d) Appreciate the extent to which statistical conclusions often reflect as much the underlying assumptions of the analysis as the features of the quantitative data used.
e) Appreciate in particular how assumptions and sample size are often substitutes in the process of generating significant results.
f) Awareness of the asymmetry often found in statistical testing: Failure to establish enough evidence for confidence in one proposition is not evidence of the opposite proposition.
Cognitive Skills:
On completion of this course students should:
a) Recognize statistical techniques appropriate to the analysis of particular circumstances.
b) Be inclined to use freely and accurately simple statistical measurements or concepts like median and covariance in appropriate circumstances.
c) Be familiar with basic principles of probability and be able to consult tables pertaining to various probability distributions.
d) Be able to design and implement simple sampling experiments with a view to achieving or approaching adequate randomness or representativeness in sample data.
e) Interpret models and associated statistics arising out of regression analysis.
Key Skills:
As a by-product of exploring the features of statistical analysis the course should:
a) Foster basic numeracy by some substantial deployment of data within statistical formulae and procedures.
b) Provide practice and awareness of calculation efficiency made available by simple calculator and spreadsheet facilities.
c) Encourage the presentation of statistical derivations and results in conventional and orderly formats.
|
Assessment Information
| 2 hour written examination worth 100% of assessment |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Topic 1: Data Summary
Topic 2: Correlation & Regression
Topic 3: Multiple Regression
Topic 4: Probability Distributions: Binomial and Normal
Topic 5: Sampling Practice and Sampling Distributions
Topic 6: Hypothesis Testing: Means & Proportions
Topic 7: Hypothesis Testing: Regression Parameters
Topic 8: Hypothesis Testing: Qualitative Variable Correlation
|
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords |
Not entered |
Contacts
| Course organiser |
Dr Inger Seiferheld
Tel: (0131 6)50 3801
Email: Inger.Seiferheld@ed.ac.uk |
Course secretary |
Mr Stuart Mallen
Tel: (0131 6)50 8071
Email: Stuart.Mallen@ed.ac.uk |
|
copyright 2011 The University of Edinburgh -
1 September 2011 5:43 am
|
University Homepage