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Member rate £492.50
Non-Member rate £985.00
Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked
*If you attended our Methods School in Summer/Winter 2024.
Thursday 28 - Saturday 30 July
10:00-12:00 and 14:00-17:00
15 hours over 3 days
This course is designed to provide critical mathematical background for applications in quantitative social science research. The course will provide an overview of the essential concepts and language required for competent analysis using quantitative approaches in social science. It can also serve as a good refresher of relevant mathematical language and approaches before participation in a main course for those with an existing mathematical background. The topics focus on dimensions of linear algebra, calculus, and probability theory that are most commonly applied in social science research. The examples are taken from social science and the instructor will emphasize the areas of applied research where each concept is used. The material will be introduced through interactive lectures with opportunities for participants to engage with the material during the sessions and through exercises between the sessions.
This course is designed to provide critical mathematical background for applications in quantitative social science research. The course will provide an overview of the essential concepts and language required for competent analysis using quantitative approaches in social science. It can also serve as a good refresher of relevant material before participation in a main course for those with an existing mathematical background. The topics focus on dimensions of linear algebra, calculus, and probability theory that are most commonly applied in social science research. Therefore instead of a comprehensive mathematical approach, the course will focus on the most critical concepts and approaches needed for deeper understanding of tools like multivariate regression, logistic regression, principle component analysis, structural equation modeling, and other statistical methods. The examples are taken from social science and the instructor will emphasize the areas of applied research where each concept is used as it is presented. The material will be introduced through interactive lectures with opportunities for participants to engage with the material during the sessions and through exercises between the sessions.
The planned structure will include:
Please inform the instructor of the main courses that you will participate in, as the content may be adapted accordingly.
Basic algebra (secondary school level)
Day | Topic | Details |
---|---|---|
Thursday | Calculus (~3 hours) |
Calculus:
Applications: identifying minimum and maximum points, optimization, convergence and divergence of series, … |
Friday | Linear algebra |
Linear algebra
Applications and notation for regression analysis |
Thursday | Functions and Notation (~2 hours) |
Functions and notation
|
Saturday | Probability theory |
Probability theory
|
Day | Readings |
---|---|
Thursday |
Timothy M. Hagle, Basic Math for Social Scientists: Concepts, Quantitative Applications in the Social Sciences 108 (Thousand Oaks, Calif: Sage, 1996), chapter 1.
Gudmund R. Iversen, Calculus, Quantitative Applications in the Social Sciences 110 (Thousand Oaks, Calif: Sage Publications, 1996), chapters 2 and 3. |
Friday |
Krishnan Namboodiri, Matrix Algebra: An Introduction, Quantitative Applications in the Social Sciences 38 (Beverly Hills: Sage Publications, 1984), pages 7-38.
Jeff Gill, Essential Mathematics for Political and Social Research, Analytical Methods for Social Research (Cambridge ; New York: Cambridge University Press, 2006), chapters 3 and 4. |
Saturday |
Jeff Gill, Essential Mathematics for Political and Social Research, Analytical Methods for Social Research (Cambridge ; New York: Cambridge University Press, 2006), chapters 7 and 8.
Tamás Rudas, Probability Theory: A Primer, Quantitative Applications in the Social Sciences 142 (Thousand Oaks, CA: Sage, 2004). |
None
None
See online sources and recommended readings on the course website.