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Quantitative Research Methods Complete Summary

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This document summarizes every detail discussed in Dr. Kai Bekker's quantitative research methods class. It includes a full summary of the five lectures, based on the uploaded PowerPoint, and provides extra context to the subjects discussed to make the material easy to understand. This summary also includes clarification of the examples that were provided in class.

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Inhaltsvorschau

Quantitative Lecture Summaries

Table of Contents
Lecture 1........................................................................................2
Lecture 2........................................................................................5
Lecture 3.......................................................................................10
Lecture 4.......................................................................................14
Lecture 5.......................................................................................22




1

,Lecture 1
Quantitative research methods revolve around answering a particular research
question by collecting numerical data and analyzing it using mathematical
methods (in particular, statistics).

Types of Quantitative Research
 Descriptive (What?): Interested in a quantitative answer or a numerical
change.
 Inferential (Why?): Test relationships or explain something.

Why do we need quantitative research?
 Quantitative research methods provide us with a toolbox for studying the
(social) world around us using the scientific method.
 Helps in minimizing cognitive assumptions that may distort our
interpretation
 Depending on the state of prior theory and research on the topic, you
have to use
quantitative methods to make a useful contribution to our understanding
of the world.
 The only way to establish a causal relationship.


Prior theory and
Nascent Intermediate Mature
research
Proposed Focused questions
Open-ended inquiry
relationships between and/or hypotheses
Research questions about a phenomenon
new and established relating existing
of interest
constructs constructs
Qualitative – open- Quantitative – focused
ended data that need Hybrid (qualitative measures
Type of data
interpretation for and quantitative)
meaning
Typically, new One or more new Mainly existing
Constructs and
constructs, few formal constructs and/or constructs and
measures
measures measures measures
Theoretical
Suggestive theory Provisional theory Supported theory
contribution

Good research questions
 Can be answered and need answering (”
So what?”)
 Improve our understanding of how the
world works
 Inform theory

What is a theory?
 A theory explains relationships among
concepts or events within boundary
conditions.
 A (good) theory simplifies and explains
complex real-world phenomena

Elements of good theory
 What: Constructs and variables that logically should be considered part of
the explanation of the phenomenon of interest

2

,  How: Propositions and hypotheses that indicate the “links” between
constructs and variables. (Typically) indicate causality
 Why: The “glue” that justifies the selection of constructs/variables and
their proposed relationships
 Who, where, when: The conditions the theory should hold. Set the
limitations of the generalizability of the theory with context, time, and
space.


TL; DR
 Good theory simplifies and explains complex real-world phenomena
 Good research questions can and need to be answered utilizing statistics
(quantitative research methods)

THE DATA GENERATING PROCESS (DGP)
 Our theoretical model is only a (small) part of the broader, more complex
data-generating process (DGP)
• To identify the variation in the data that answers our research question,
we need to make credible claims about the complete DGP.

Promotion versus prevention-focused questions




Building a model
During the early phases of our research, we might assume that a variable relates
to another variable. In practice, this relationship is not feasible or as simple as it
might seem.

Alternative explanations:
• They are likely part of the DGP
• They can also explain our proposed relation but
for different reasons (different how and/or why)
We must find clever ways to rule out these alternative
explanations to identify (credibly test) our proposed
theoretical relation with the data. This is a large part
of the scientific review process.

Research design
A good research design helps us achieve this by:


3

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