Publishing Your First Quantitative Paper

A Practical Guide to Writing, Analyzing, and Presenting Social Science Research

1 Details

Instructor: Bogdan G. Popescu
Prerequisites: None

2 Course Description

This course is an intensive, hands-on introduction to writing a research article in the social sciences, with a focus on political science, sociology, or economics. Students will be taught to use R, R Studio, Quarto, Markdown, and Jabref.

By the end of the course, students will have developed and refined a complete research paper through a series of iterative assignments and structured feedback. The course integrates methodological training, substantive readings, and practical writing skills. Course content is divided into weekly units covering both technical skills and theoretical content.

This is the visual roadmap of the course:

Topic → Proposal → Methods → Analysis → Paper Draft → Feedback → Final Paper → Website

3 Learning Outcomes

Upon successful completion of this course the students will be able to:

  • Develop a research question and transform it into a publishable paper.
  • Master essential academic tools including reference managers (e.g., JabRef), markdown-based word processing, and professional presentation software.
  • Understand and apply core methods in social science research, including qualitative comparative analysis, difference-in-differences (DiD), and regression discontinuity design (RDD).
  • Write each section of a paper: abstract, introduction, argument, methods, literature review, findings, discussion, and conclusion.
  • Conduct basic quantitative analysis in R, including data merging, regression modeling, and visualization.
  • Create a personal academic website using GitHub Pages to showcase their work.

4 Example Paper

The research paper should provide an extensive background on the topic and a clear contribution to the literature. The analysis should include some quantitative analysis to test hypotheses. The statistical part of the research project involves using data (collect and prepare the data to run quantitative analyses and produce graphs) and a specialized software (R). You can download the template for the paper at this link. You are welcome to tweak the template in any way you like. Check out lecture 2 to understand the paper structure better.

5 Example Paper Presentation

You can download the template for the paper presentation at this link. This should provide a good starting point for the type of information that needs to be included in the presentation. You are welcome to tweak the template in any way you like. Check out lecture 4 to understand the presentation structure better.

Lecture 1

The Topic and Research Question Slides

  • Topic vs. Research Question
  • How to find a Topic and a Research Question
  • Good and Bad Research Questions

Lecture 2

Essential Tools for Writing a Paper Slides

  • Jabref
  • Quarto
  • Article Template

Lecture 3

Operations and Objects in R Slides

  • Quarto Notebooks
  • Operations and Objects in R

Lecture 4

Quarto Presentations Slides

  • Presentations in Quarto
  • Presentation themes in Quarto
  • Image and Video Backgrounds
  • Code Blocks

Lecture 5

Intro to Statistics Slides

  • Variables
  • Samples and Population
  • Data

Lecture 6

Working with Data in R Slides

  • Dataframes
  • Lists
  • External Files
  • Paths

Lecture 7

Dplyr and Basic Visualization Slides

  • Merging Data
  • Scatterplots

Lecture 8

Visualizing Data Distributions in R Slides

  • Histograms
  • Barplots
  • Lineplots

Lecture 9

Modeling Relationships Between Variables Slides

  • Correlations
  • Bivariate Regressions

Lecture 10

Interpreting Binary and Multivariate Regression Models Slides

  • Dummy Variables
  • Interactions
  • Multivariate Regressions

Lecture 11

Differences in Differences Slides

  • Differences in Differences
  • Exploring Binary Variables
  • Interaction Effects

Lecture 12

Regression Discontinuity Design Slides

  • Identifying Local Effects Using Arbitrary Thresholds
  • Regression Discontinuity Designs and Causal Effects

Lecture 13

Data Visualization in R - 1

  • Color contrasts
  • Principles of ggplot
  • Aesthetics and geoms
  • Labels and Facets

Lecture 14

Data Visualization in R - 2

  • Barplots
  • Uncertainty
  • Boxplots and Violin Plots
  • Annotations
  • Temporal Plots

Lecture 15

The Abstract and the Argument Slides

  • Writing the Abstract and the Argument
  • Types of Abstracts
  • Conceptual Definitions
  • Hypotheses
  • Dependent and Independent Variables

Lecture 16

Literature Review Slides

  • Writing the Literature Review
  • Sources
  • Types of Literature Reviews

Lecture 17

Methods Slides

  • Research Designs
  • Quantitative vs. Qualitative Research Designs
  • Types of Research Designs

Lecture 18

Findings, Discussion, Intro, and Conclusion Slides

  • Structuring and presenting your findings
  • Crafting a strong discussion section
  • Finalizing your paper

Lecture 19

Making a website on GitHub: username.github.io

  • Making a website on Quarto
  • Storing a website on GitHub
  • Structuring a professional website for Data Analytics Jobs