Week 1: Introduction

POP88162 Introduction to Quantitative Research Methods

Tom Paskhalis

Department of Political Science, Trinity College Dublin

Overview

Assistant Professor in Political Science and Data Science, Trinity College Dublin
- Before: Postdoctoral Fellow, New York University
- PhD in Social Research Methods, London School of Economics and Political Science
My research:
- Political communication, social media, interest groups
- Computational methods, text analysis, machine learning
Contact
- tom.paskhalis@tcd.ie
- tom.paskhal.is

Hannah Frank

Lucas Da Silva

PhD student, Trinity College Dublin
Research interests:
- Ideologies, political media, business political activity, polarisation, and voting behaviour
- Experiments, quasi-experiments, quantitative text analysis, and machine learning
Contact
- ldasilva@tcd.ie

Introductory module - no formal prerequisites
Laptop with Windows/Mac/Linux OS
Software:
- R (version 4+) - statistical programming language
- RStudio - feature-rich R editor

Lectures:
- Tuesday 09:00-11:00 in 2043 Arts Building
Workshops:
- Tuesday 13:00-14:00 in M20 Museum Building
Tutorials:
- Group 1 - Thursday 09:00-11:00 in 1014 Arts Building
- Group 2 - Thursday 16:00-18:00 in AP0.12 Aras an Phiarsaigh
Office Hours:
- Thursday 11:00-13:00 in-person or online
+ Readings
+ Assignments

Core books:
- Alan Agresti. 2018. Statistical Methods for the Social Sciences. 5th ed
- Ethan Bueno de Mesquita and Anthony Fowler. 2021. Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis
Very good additional texts:
- Andrew Gelman, Jennifer Hill and Aki Vehtari. 2020. Regression and Other Stories
- Kosuke Imai. 2017. Quantitative Social Science: An Introduction
More choices and week-by-week reading list in the syllabus.

Participation (10%)
- Tutorial attendance, RQ presentation
3 R assignments (5% each)
Research design (15%)
- Approximately 1-2 pages and no more than 500 words
Research paper (60%)
- Must set up, perform, and interpret at least one test of statistical significance
- Approximately 10 pages and no more than 5,000 words
- Due by 23:59 Tuesday, 22 April 2025
Submission via Blackboard

All submitted coursework must be individual and original.
Reference any literature you use in the correct manner
- You can use Chicago Manual of Style or APSA Style Guide (its derivative) for citing correctly.
Check College’s avoiding plagiarism guide: https://libguides.tcd.ie/plagiarism/.

If you are carrying out research on human subjects (interviews, surveys, experiments, etc.),
Then you must first receive ethical approval from TCD!
More information is available here: https://www.tcd.ie/ssp/research/ethics/

Week	Date	Lecture Topic	Workshop Topic	Tutorial Topic	Assignment Due
1	21 January	Introduction	R Overview	Getting Started with R
2	28 January	Descriptive Statistics	Data Structures	Data & Variables
3	4 February	Probability Theory	Probability Distributions	Distributions & Sampling	1 R Assignment
4	11 February	Hypothesis Testing	Data Frames	Data Frames & Plotting
5	18 February	Analysis of Proportions & Means	Factor Variables	Cross Tabulation
6	25 February	Correlation	Visualisations	Correlation	2 R Assignment
7	4 March	-	-	-	-
8	11 March	Linear Regression I	RQ Presentations I	Linear Regression I
9	18 March	Linear Regression II	RQ Presentations II	Linear Regression II
10	25 March	Linear Regression III	RQ Presentations III	Linear Regression III	3 R Assignment
11	1 April	Causation	RQ Presentations IV	Causation
12	8 April	Logistic Regression	RQ Presentations V	Logistic Regression	Research Design