Core
4
6 ECTS
Autumn
None
EC 170
Amer Demirovic
2017
Descriptive statistics: analyse single data series and correlation between series
Probability: simple probability, conditional probability and independence, Bayes’ theorem
Discrete random variables: expected value and variance of discrete random variables, binomial random variables, probability distributions
Continuous random variables: Normal Probability Distribution, finding normal probabilities
Distributions of sampling statistics: Central Limit Theorem, sample mean, sample variance, sample proportion
Testing of statistical hypotheses: hypothesis tests and significance levels, tests concerning means, differences in means and variances
| Type | Number per Term | Duration | Total Time |
|---|---|---|---|
|
Lectures |
15 | 1.5 | 22.5 |
|
Workshops |
5 | 1.5 | 7.5 |
|
Seminars |
5 | 1.5 | 7.5 |
| Tutorials | 5 | 1.5 | 7.5 |
| Total Guided/Independent Learning Hours | 45.0 | ||
| Total Contact Hours | 105.0 | ||
| Total Engagement Hours | 150.0 | ||
| Type | Number Required | Duration / Length | Weighting | Timing / Submission Deadline |
|---|---|---|---|---|
|
Computer based test |
1 |
1 hour |
15% |
Week 4 |
|
Mid-semester exam |
1 |
2 hours |
20% |
Week 8 |
|
Written Test |
1 |
1 hour |
15% |
Week 12 |
|
Final exam |
1 |
3 hours |
50% |
Week 17 |
Intended Learning Outcomes:
To enhance comprehension of the most important terminology related to usage of statistics in the study and application of economics.
To appreciate and adapt to the “compromises” in economic applications in the real world
Statistically analyse the distribution of data series
Estimate mean and variance/standard deviation of random variables
Analyse the correlation between variables
Estimate unconditional and conditional probability of occurrence of events
Define and test basic statistical hypotheses
Understand the importance of randomness in economics and finance
To apply already defined methods to judge the reliability of data
Teaching and Learning Strategy:
A variety of approaches to managing the learning process is introduced in order to be able to meet the ILOs. Teaching will be predominantly based on lectures. Lectures will primarily focus on the key text book. In addition to the key text book, supplementary resources will be used. (ILO: 1-9)
Learning is organised and supported to encourage active learning, for example by in-class exercises and computer-lab exercises. The problems will be firstly solved by professor, and after that students will be given opportunity to solve problems. (ILO: 1-9)
Assessment Strategy:
Computer based test (ILO: 3-4)
Midterm exam (ILO: 3-6)
Written test (ILO: 7)
Final exam (ILO: 1-9)
Practical Skills:
To notice and understand complex economic relationships
Ability to infer basic probabilistic estimates of population from a sample
Ability to recognise and apply statistical models
Basic use of statistics to analyse problems in economics and finance
Teaching and Learning Strategy:
Lectures (PS: 1-4)
Tutorials (PS: 1-4)
Computer lab exercises (PS: 1-4)
Assessment Strategy:
Final Exam (PS: 1-4)
Computer based test (PS: 1-4)
Transferable Skills:
Data and facts analyses skills
Compare, inspect or record facts
Numerical Skills
Communication Skills
Teaching and Learning Strategy:
Lectures (TS: 1-4)
In-class exercises (TS: 1-4)
Tutorials (TS: 1-4)
Computer lab data analysis (TS: 1-3)
Assessment Strategy:
Midterm/Final Exam (TS: 1-4)
Computer based test (TS: 1-3)
In-class exercises (TS: 1-4)
Set text
Keller, G. and Gaciu, N. (2015) Managerial Statistics, 1st EMEA Edition, Cengage Learning
Supplementary Materials
Barrow, M., (2013), Statistics for Economics, Accounting and Business, 6 Edition, Pearson
Hand, D., (2008), Statistics, a Very Short Introduction, Oxford University Press
James, G., et al., (2016), An Introduction to Statistical Learning, Springer
Newbold, P., et al., (2012), Maths for Business and Economics, 8 Edition, Pearson
Renshaw, G., (2016), Maths for Economics, 4 Edition, Oxford University Press
Please note
This specification provides a concise summary of the main features of the module and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided.
More detailed information on the learning outcomes, content and teaching, learning and assessment methods of each module and programme can be found in the departmental or programme handbook.
The accuracy of the information contained in this document is reviewed annually by the University of Buckingham and may be checked by the Quality Assurance Agency.
Date of Production : April 2017
Date approved by School Learning and Teaching Committee:
Date approved by School Board of Study :
Date approved by University Learning and Teaching Committee:
Date of Annual Review:
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