Chapter 3 - Theory and Causality Flashcards
Two Goals of Social Science
- Explain change over time
2. Explain variation
Explanation of Variation
If there is variation. there MUST be an independent variable that causes it.
Theory Definition and the Explanations of Theorists
A system of ideas; condenses and organizes knowledge
Theorists explain that events are related, how they are related, and why
Concept Definition and One Example
Abstract representation of phenomenon
Ex.: Political interest, political knowledge
Hypotheses Definition
Statement of anticipated relationship between concepts
3 Characteristics of a Useful Hypothesis
- Clear state of relationship between two variables
- What is the effect and which comes first?
- Falsifiable
3 Errors in Causal Reasoning
- Correlation doesn’t equal causation
- Mixing temporal order (cause and effect mixed up)
- Post-hoc fallacy - before doesn’t mean it is the cause
Positive Relationship
Both concepts more in the same directions (more of a will result in more of b)
Negative Relationship
Concepts move in opposite direction
A goes up, B goes down, vice versa
Operationalization
Moving from abstract (synonymous with concept??) to concrete
Ex.: Student effort = hours studying
Null Hypothesis
Any pattern between the two concepts observed in data is due to chance (default assumption)
There is no relationship between A and B.
Replication ensures a constant test of the null hypothesis.
Alternative Hypothesis
Pattern between the two concepts observed in data is not due to chance
Falsifiability
In order for a hypothesis to be useful, we have to imagine a scenario in which we could prove it wrong.
Five Criteria of Causality
- Correlation
- Plausible
- Temporal Order
- Not spurious (both caused by a third confounding variable)
- Consistent (reproducible)
Confounding Variable
Extraneous variable that affects both of the correlated variables and makes it seem like there is a relationship between them
The Conclusion we must come to if we can’t reproduce results
It’s not useful for there is an assumption that, as theory builds, we get more and more confident in the hypothesis
Internal Validity
Results are reality based within the confines of the study.
Basically, we’ve met the criteria of causality.
Observational v Experimental Data
Observational data researchers don’t influence the population/thing in any way, and it can only be used to establish association.
Experimental data is derived when researchers directly intervene to alter variables (give one group placebo, one real thing). Can establish causality.
Applied v Basic Research
Basic research is scientific research aimed to improve scientific theories for improved understanding or prediction of natural or other phenomena whether or not the results have immediate or obvious applications.
Applied research indicates that the research addresses a topic or problem in the real world.
Proposition
States that, if the hypothesis is true, the following predicate of a subject is either true or false.
(Ex.: if mental illness causes creativity, those with OCD will be creative)
Continuum
Used when classifying variables that can be ordered or ranked.
Ideal Type
A means of classifying concepts in which a non-existent ideal is outlined and observed cases are then compared with this ideal.
Typology
Th classification of things on the basis of their characteristics (e.g. a typology of political party system based on the number of competitive parties in the system)
The classification of observations in terms of their attributes on multiple variables. Such classification is usually done on a nominal scale.
Hypothesis-Testing
A method used in statistics to test the validity of a statement by comparing expected results with empirical or observed results; typically involves testing the null hypothesis and, based on the results, deciding whether to accept or reject it.
