Undergraduate Course: Statistical Methods for Economics (ECNM08016)
Course Outline
| School | School of Economics |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The course is intended as an introduction to probability theory and statistics for economists and other social science students. It is a required course for students intending to proceed to an Honours degree involving Economics. |
| Course description |
The topics covered will include:
Basic concepts, sample spaces, events, probabilities; Conditioning and independence, Bayes' formula; Discrete random variables, expectation, variance, mean, independence; Continuous random variables, distributions and densities; Covariance, correlation, central limit theorem; Summary statistics; Sampling distributions; Hypothesis testing; Interval estimation; simple linear regression, multiple regression, and logistic regression.
The use of Excel for statistical analysis will be supported through material available on the course website.
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Information for Visiting Students
| Pre-requisites | A knowledge of calculus and an Economics course taken previously, or permission of the course organiser. |
| 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: 1 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 13.5,
Summative Assessment Hours 3,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
159 )
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| Assessment (Further Info) |
Written Exam
85 %,
Coursework
15 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Weekly Homework: 5%
Midterm Exam: 15%
Group Project: 10%
Final Exam: 70%
Projects: Bonus Marks
Resit Exam: 100% (August Diet).
Final mark for visiting students as above. |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | | 2:00 | | | Resit Exam Diet (August) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- A knowledge and understanding of probability and statistical methods with applications to economic and social issues.
- Research and investigative skills such as problem framing and solving and the ability to assemble and evaluate complex evidence and arguments.
- Communication skills in order to critique, create and communicate understanding and to collaborate with and relate to others.
- Personal effectiveness through task-management, time-management, teamwork and group interaction, dealing with uncertainty and adapting to new situations, personal and intellectual autonomy through independent learning.
- Practical/technical skills such as, modelling skills (abstraction, logic, succinctness), qualitative and quantitative analysis, and general IT literacy.
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Reading List
| Diez, Barr, and Çetinkaya-Rundel "OpenIntro Statistics", Latest Edition |
Additional Information
| Graduate Attributes and Skills |
See Learning Outcomes |
| Additional Class Delivery Information |
One lecture per week each lasting 2 hours, one weekly 1.5 hour tutorial to be arranged in addition. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Nicholas Myers
Tel: (0131 6)51 5189
Email: |
Course secretary | Ms Dawn Mcmanus
Tel: (0131 6)50 6946
Email: |
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