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Samenvatting

Summary Quantitative Research Methods VU 2024 (premaster)

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2023/2024

this is a summary of the lectures given, preparation for the lectures through the book and clear explanations of difficult points.












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Wat is er van het boek samengevat?
Week 2 & 3
Geüpload op
16 mei 2024
Aantal pagina's
62
Geschreven in
2023/2024
Type
Samenvatting

Onderwerpen

Voorbeeld van de inhoud

Quantitative research methods
Pre-master Vrije Universiteit Amsterdam




Index
Week 1 ............................................................................................................................................................. 2
Lecture 1 ............................................................................................................................................................. 2

Week 2 ............................................................................................................................................................. 7
Preparation – Chapter 3 describing variables .................................................................................................... 7
Types of variables .......................................................................................................................................... 7
Distribution .................................................................................................................................................... 8
Summarizing the distribution ........................................................................................................................ 9
Lecture 2 ........................................................................................................................................................... 11

Week 3 ........................................................................................................................................................... 20
Preparation – chapter 4 describing relationships ............................................................................................. 20
Lecture 3 ........................................................................................................................................................... 21

Week 4 ........................................................................................................................................................... 30
Lecture 4 ........................................................................................................................................................... 30
Statistical tests ............................................................................................................................................. 30
Chi-square test & Logit regression ............................................................................................................... 35
Testing hypotheses ...................................................................................................................................... 37
Parts of the t-test ......................................................................................................................................... 38

Week 5 ........................................................................................................................................................... 50
Lecture 5 ........................................................................................................................................................... 50
Exam preparation ............................................................................................................................................. 56
Example questions ............................................................................................................................................ 56




Exam
- Understanding concepts
- Applying concepts to questions
- Interpreting R output

Exam material:
- Lecture slides
- Required readings of textbook https://theeffectbook.net/introduction.html

,Week 1
Lecture 1

WHAT is quantitative research?
Quantitative research methods revolve around answering a particular research question by
collecting numerical data that are analyzed using mathematical methods (in particular,
statistics)

Types of quantitative research questions:
1. Descriptive (what?)
This type of quantitative research seeks to describe characteristics of a population or
phenomenon being studied. It does not answer questions about how/when/why the
characteristics occurred, but rather "what" is occurring.
→ Interested in a quantitative answer: ‘’how many students are enrolled
in the premaster?’’
→ Interested in a numerical change: ‘’are the numbers of students rising
compared to last year?’’

2. Inferential (why?)
This research type goes beyond describing to making inferences about a larger
population based on data collected from a sample. It is used to assess the results of
specific conditions or effects from a smaller group to a larger one.
→ Test relationships: ‘’what is the relation between self-esteem and
average grade?’’
→ Explain something: ‘’what factors cause changers in performance?’’


WHY do we need quantitative research?
- In essence, quantitative research methods provide us with a toolbox to study 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.
- Only way to establish causal relationship.



Trust your intuition: the curse of belief bias

,WHEN do we need quantitative research?




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 is an explanation of relationships among concepts or events within a set of
boundary conditions.
→ A (good) theory simplifies and explains complex real-world phenomena.

, Elements of a good theory (Whetten, 1989)
WHAT Constructs and variables that logically should be considered part of the
explanation of the phenomenon of interest.

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 = theoretical rationale

WHO, the conditions under which the theory should hold. Set the limitations
WHERE, of the generalizability of the theory wrt context, time, and space
WHEN = scope and boundaries



WHO, WHERE, WHEN




HOW
WHAT




WHAT



WHY




HOW




Summary (TLDR = Too Long Didn’t Read)
- A good theory → simplifies and explains complex real-world phenomena.

- Good research questions → can and need be answered by means of statistics
(quantitative research methods).

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