Class notes
MCRS week 1 till 5
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In this document you will find a summary of all course material treated from week 1 to 5 for the course MCRS, for both the methods part and the statistics part.
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METHODS week 1Scientific research is a systematic process of gathering theoretical knowledge through
observation (empiricism). Requirements of a research: it needs to be empirical, based on
social reality, systematic, cumulative, public, verifiable and open to criticism. And last it
needs to be objective and predictive.
Reasons for research
- Fundamental research: There is a knowledge gap we want to fill by testing a theory.
We want to contribute to science.
- Applied research: We observe in a systematic way. We want to acquire knowledge to
solve a practice problem.
The process
You start with a research questions. Based on your research question you come up with a
research strategy and then you choose a specific design. After that you are going to
decide which data collection method you need to be able to answer your question.
- Different research questions depending on if we are interested in an effect or
association.
- Quantitative (measuring/numbers/values/test theory) / Qualitative (words/generate
theory).
- Experimental (quantitative, to look into effect) / Cross-sectional or Longitudinal
(qualitative, to see if there is a correlational, an association).
- Observation / Posing questions / Content analysis
METHODS week 2
Ontology
What really is it? Is there an underline reality to something or is there not? What is?
Objectivism: The underlying reality has the characteristics of an object, we can measure.
Constructionism: Social entities are considered social constructions, not objects. We
can’t measure this objectively. It is based on your interpretations.
Epistemology
Questions of how communication should be understood. How do we get knowledge?
Through observations (empiricism) or by logical reasoning (rationalism).
Positivism: There is an object you can measure. It is about empiricism that leads to
specific predictions, hypothesis.
Interpretivism: It is about understanding what is going on.
Two approaches
- Empirical-Analytical: Based on positivism, objectivism, quantitative,
experiment/survey/content analysis.
- Empirical-Interpretive: Based on interpretivism, constructionism, qualitative, individual
interviewers/focus group interviews/ethography.
Scientific method
A theory is a overarching explanation of many related phenomena. An hypothesis
explains a pattern or general relation between observations.
1. Empirically testable (observations)
1
, 2. Replicable (repeatedly)
3. Objective (independently)
4. Transparent (replicable by anyone)
5. Falsifiable (contradiction possible)
6. Logically consistent (internally consistent)
Universalistic (general) Particularistic (specific)
Fundamental (to know) frequent rare
Applied (to help) rare frequent
The empirical cycle
1. Observation: noticeable relations and questions.
2. Induction: from specific (observations) to general, theories that can explain the
(specific) relations (empirical-interpretive).
3. Deduction: from general to specific, formulating (specific) expectations/hypothesis that
can be tested (empirical-analytical).
4. Testing: testing the variables from the hypothesis.
5. Evaluation: do the results support the hypothesis that were formulated on the basis of
theory.
Problem definition
1. The research question: the main question, descriptive, explanatory or predictive.
2. The research objective: the goal of your research.
3. Theoretical framework: hypothesis and conceptual model.
One tailed hypothesis: you have a specific expectation about the direction of the effect.
Two tailed hypothesis: you don’t have a specific expectation about the direction of the
effect.
Conceptual model and relationships
A conceptual model is a schematic overview of your hypothesis.
- Asymmetrical: one variable affects or predicts the other variable.
- Symmetrical: association, relationship between two variables.
METHODS week 3
Building blocks of hypothesis
- Units of analysis/cases: all subjects or objects that are mentioned.
- Variables: characteristics of the units of analysis.
- Values: possible categories per characteristic.
Operationalization
Making your variable measurable. Manifest variables are directly measurable. Latent
variables aren’t directly measurable.
1. Come up with measurable definition of the concept
2. Choose indicators
3. Develop questions/statements
4. Assign measurements scales: Yes/no scale (categorical/nominal variables). Likert
scale. Semantic differential scale.
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