Undergraduate Course: Mathematics for Social Science (SSPS08009)
Course Outline
| School | School of Social and Political Science |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Not available to visiting students |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Credits | 20 |
| Home subject area | School (School of Social and Political Studies) |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | Laying Mathematical Foundations for Quantitative Methods
This course aims to provide students in the with Quantitative Methods programmes with the mathematical foundations, which will allow them to fully explore advanced methods, as well as gain a full understanding of the mathematic principles behind the basic methods. Throughout the course, the application of mathematics to social science research problems will be emphasised.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Higher/A Level Maths at B required. |
| Additional Costs | None |
Course Delivery Information
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| Delivery period: 2014/15 Semester 1, Not available to visiting students (SS1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
| Course Start Date |
15/09/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 22,
Seminar/Tutorial Hours 11,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
163 )
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| Additional Notes |
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| Breakdown of Assessment Methods (Further Info) |
Written Exam
85 %,
Coursework
15 %,
Practical Exam
0 %
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| No Exam Information |
Summary of Intended Learning Outcomes
1. Social science problem solving with formal mathematic thinking
2.To have an understanding of the following topics
-Gradients, equations and graphs of straight lines
-Least squares estimation of slope and intercept
-Integration
-Differentiation
-Differential equations
-Calculus of more than one variable
-Vectors
-Matrices
-Graphs of quadratic functions, the solution of quadratic equations by computing the square and by the formula
-Exponential and logarithmic functions
-Radian measure and trigonometric functions
-Curve sketching
-Eigenvalues and eigenvectors
-Principal components
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Assessment Information
| 15% continuous assessment based on the best four out of five fortnightly tutorial assignments. This will constitute a formative feedback event. 85% written open-book two hour exam at the end of the course. |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
In the first part (weeks 1-5), the course will address linear relationships, integration and differential equations and least squares estimation of slope and intercept.
In the second part (weeks 6-8), the course looks beyond linearity to quadratic, exponential and logarithmic functions. This will include eigenvalues and eigenvectors, and principal components. The algebra of basic probability will be included here, laying the basis for dealing mathematically in later years of the programme with statistical distribution functions and with statistical inference.
In the third and final part (weeks 9-10), students will cover issues to do with curve sketching and analysis of residuals. They will also gain an understanding of the applications and relevance of the mathematical principles covered for future quantitative analysis methods and statistical inference.
Part A. Straight Lines
Week 1: Introduction and recap of required knowledge
Week 2: Gradients, equations and graphs of straight lines
Week 3: Tangent lines, differentiation
Week 4: Derivative functions, integration
Weeks 5: Least squares estimation of slope and intercept
Part B. Beyond Linearity
Week 6: Graphs of quadratic functions, the solution of quadratic equations by computing the square and by the formula
Week 7: Exponential and logarithmic functions, radian measure, and trigonometric functions
Week 8: Eigenvalues and eigenvectors, and principal components
Part C: Looking Ahead
Week 9: Curve sketching and residual analysis
Week 10: Summary and relevance for social sciences
Week 11: Conclusion & revision
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| Transferable skills |
Not entered |
| Reading list |
Students will be invited to make use of both on-line resources and books.
http://www.socialsciences.manchester.ac.uk/subjects/economics/postgraduate-taught/pre-session-maths/
Croft, A. and Davison, R. 2006. Foundation Maths. 4th ed., Longman.
Haeussler, E.F., Paul, R.S. and Wood,R., 2014. Mathematical Analysis for Business, Economics and the Life and Social Sciences, 13th ed., Pearson
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| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Valeria Skafida
Tel: (0131 6)51 3215
Email: Valeria.Skafida@ed.ac.uk |
Course secretary | Mr Edwin Cruden
Tel: (0131 6)51 5197
Email: Edwin.Cruden@ed.ac.uk |
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© Copyright 2014 The University of Edinburgh - 29 August 2014 4:46 am
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