Skip to content

From Concepts to Variables

Agenda

  • Theory
    • Presentation & Discussion
    • Dependent and Independent Variables
  • Application
    • Concepts, & Variables
    • ANES Data Overview
  • Code
    • Student Group Live Demo: Typst for Scientific Writing (Group 1)
    • Environment & Configuration Check
    • First Steps in Python (01_getting_started.py)

Theory

Presentation & Discussion

Concepts & variables, and indicators?

Political participation, ideology, partisanship, polarization, among other, are common phenomena studied in Political Science. There is no clear definition of each of those concepts and how they are defined will vary across researchers.

Concepts provide the overarching themes or ideas that guide political analysis, while variables are the measurable elements that allow researchers to explore and examine these concepts empirically.

The process of turning abstract concepts into measurable variables is called operationalization. We'll talk more about this next week!

There are two important types of variables for your research projects:

Variables

  • The dependent variable (DV) is the effect. Its value depends on changes in the independent variable. It is also called the explained variable or the outcome variable.
  • The independent variable (IV) is the cause. Its value is independent of other variables in your study. It is also know as the explanatory variable or exogenous variable(s).

Operationalization

Operationalization means turning abstract concepts into measurable observations. Although some concepts, like age, turnout or party affiliation can more easily be measured, others, like political ideology, knowledge, or cynicism can be more difficult.

Through operationalization, you can systematically collect data on processes and phenomena that aren't directly observable.

Operationalization example

The concept of political ideology can't be directly measured, but it can be operationalized in many different ways. For example:

  • self-rating scores on an ideological scale (e.g., from very liberal to very conservative)
  • aggregating attitudes on key political issues (e.g., taxation, healthcare, immigration)
  • recent votes cast for candidates from specific political parties

Application

Explore the relationship between concepts

  1. Identify and explore the relationship between the concepts in your first Milestone. When you have identified and slightly defined your concepts you can analyzed them in following ways:

    • Strength of relationship: degree to which two or more concepts are related.
    • Sign of relationship: are concepts positively or negatively related to each other?
    • Direction of relationship: the types of relationship that categories exhibit. *
      • "If X then Y"
      • "X implies Y"
      • "X occurs before Y"
      • "X is the primary cause of Y"
      • "X motivates Y"
      • ...

  2. With regards to your identified concepts, identify potential variables that you could use in the ANES codebook.

Code: Live Demo & Hands-on Lab

Student Group Live Demo (Group 1)

Configuration & Environment Check

Before running code, let's verify that everyone's local programming setup works seamlessly:

  1. Verify VS Code and Environment:
    • Open VS Code and open your course folder (File → Open Folder...).
    • Open the Command Palette: press F1 (or click the search bar at the very top of VS Code):
      • On macOS: press Cmd+Shift+P
      • On Windows: press Ctrl+Shift+P
    • Type Python Select Interpreter and ensure .venv-da is selected. (Note: The setup script automatically configures your workspace to select .venv-da and enables full trust).
    • Look at the bottom-right status bar: it should display Python 3.12... ('.venv-da': venv).
    • (If VS Code prompts about workspace trust, click Yes, I trust the authors to ensure extensions and code execution are active).
  2. Test Smart Send (Interactive Terminal):
    • Create a new file named test.py or open 01_getting_started.py.
    • Place your cursor on the first line and run it using Smart Send (Shift+Enter).
    • Success check: An interactive Python terminal opens at the bottom of your screen and executes the code.

Hands-on Practice: Getting Started with Python

  • Follow 📘 Running Python Scripts in VS Code to practice working with interactive Python scripts.
  • Download and open 01_getting_started.py from the course materials.
  • Practice running code line-by-line using Smart Send (Shift+Enter).
  • Connecting Theory to Data: Work with your group to search candidate variables in the ANES 2024 codebook that can operationalize your project's theoretical concepts.

Get Ready for Next Session: Think. Explore. Practice.

Think

Explore

Practice

  • Refine your research puzzle based on instructor feedback from Milestone 1 and keep your .bib references organized.
  • Download and run 01_getting_started.py in VS Code to gain confidence executing Python code interactively.