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First Year: Quantitative Methods Component in Politics Prelims (PPE & History and Politics) | Courses

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First Year: Quantitative Methods Component in Politics Prelims (PPE & History and Politics)

The purpose of the methods component in Prelims is to enable students to assess and critically evaluate better assertions, theories, arguments and opinions expressed in the substantive papers of their degree [component b of the paper]. Throughout the first year, PPE and History & Politics students encounter statements accompanied by quantitative analyses aimed to provide a backing of theoretical statements with empirical evidence. Our knowledge and understanding of politics is largely contingent upon the confirmation or refutation of these statements by the empirical evidence. Statistical tools are essential for researchers to test their claims against the empirical evidence. Basic concepts of statistics, especially randomness and averaging, provide the foundations for measuring concepts, designing studies, estimating quantities of interest and testing theories and conjectures.

This methods component is a gentle introduction to the scientific methods. It consists of an 8-week route to the research cycle. Using a running example in the literature, we go through all the steps, from finding a research question up to preliminary statistical analysis. The objective is to learn how statistical methods can help us to address questions of theoretical and/or policy interest. By the end of the course, students will be in position to:

  1. critically read and evaluate statements about causal relationships based on some analysis of data;
  2. summarize quantitative information using software packages like STATA or R and assess the level of uncertainty accompanying these summary estimates.          

One can only learn statistics by doing statistics, so the course includes a four-week, hands-on, laboratory component,  where students are introduced to powerful statistical software (Stata or R).

Lecture Slides form Michaelmas Term 2015

Lecture Slides (PDFs)

HT16 Lecture 1

Week 1: Introduction and Research Design (Prof. A. Eggers)

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HT16 Lecture 2

Week 2: Concepts and Measurement (Prof. A. Ruggeri)

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HT16 Lecture 3

Week 3: Data Visualization and Descriptive Statistics (Prof. A. Ruggeri)

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HT16 Lecture 4

Week 4: Case Selection (Prof. R. Harding)

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HT16 Lecture 5

Week 5: Bivariate Relationships (Prof. A. Eggers)

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HT16 Lecture 6

Week 6: Multivariate Relationships (Prof. A. Eggers)

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HT16 Lecture 7

Week 7: Inference (Prof. A. Eggers)

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HT16 Lecture 8

Week 8: Synthesis and Review (Prof. R. Harding)

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Lab Resources

Lab 1

Lab 1: Slides

Lab Session 1

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Lab 1: Handout

Lab Session 1 Handout

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Lab 1: Worksheet

Lab Session 1 Worksheet: R Basics

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Lab 1: Data Set

The Lijphart Dataset used in all of the labs

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Lab 2

Lab 2: Slides

Lab Session 2

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Lab 2: Worksheet

Lab Session 2 Worksheet: Descriptive Statistics

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Lab 3

Lab 3: Slides

Lab Session 3

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Lab 3: Worksheet

Lab Session 3 Worksheet: Regression Analysis I

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Lab 4

Lab 4: Worksheet

Lab Session 4 Worksheet: Regression Analysis II

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Essay Guidelines

In order to complete the Political Analysis part of the Politics Prelims course you are required to submit an essay.

See the PDF for full details.

Political Analysis Essay Guidelines