POL50070 Quantitative Methods I (CORE)

Academic Year 2023/2024

Exclusively for SPIRe PhD students, this foundational module initiates the quantitative methods sequence. It covers vital statistical analyses, from data visualization to multiple regression. Emphasizing the linear regression model, students learn applied statistical analysis with real social science data.

Practical skills in R programming for political science research are imparted. Addressing assumptions, estimation, and inference in linear regression, students enhance analytical robustness.

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Curricular information is subject to change

Learning Outcomes:

Upon course completion, students will be well-prepared to:

- Master fundamental quantitative methods, from basic analysis to advanced regression, effectively conveying numerical data.
- Evaluate published research critically, applying linear models skillfully.
- Translate concepts from class into programming skills in R and LaTeX, aligning with industry and academia norms.

Indicative Module Content:

The curriculum will cover these key areas:
• Exploring and manipulating data
• Linear regression analysis
• Logit and Probit models
• Model specification and diagnostics
• Dummy variable and interactions

Student Effort Hours: 
Student Effort Type Hours
Lectures

15
Computer Aided Lab

12
Autonomous Student Learning

200
Total

227
Approaches to Teaching and Learning:
Each week's sessions comprise lectures and labs. The lectures cover the fundamental aspects of statistical inference, and will make use of small group exercises to encourage students to work directly with example material. The homework assignments are strategically designed to progressively culminate in a comprehensive regression analysis, effectively applying the technical concepts covered in the course. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: In-class final examination Unspecified No Graded No

30
Assignment: Homework assignments Throughout the Trimester n/a Graded No

40
Examination: In-class examination Unspecified No Graded No

30

Carry forward of passed components
No
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Feedback will be provided within 20 days from submission, as per university guidelines.

– Kosuke Imai. 2017. Quantitative Social Science: An Introduction. Princeton: Princeton University Press.
– Kellstedt, Paul, and Guy Whitten. 2018. The Fundamentals of Political Science Research, 3rd Edition.
- Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables, Volume 7.
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Autumn
      
Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Thurs 14:00 - 15:50