Chapter 2 Flashcards
testability
- Researchers should be able to put scientific theories to empirical tests
- It is particularly important that theories are falsifiable
deductive line of reasoning
going from theory -> hypothesis -> prediction
inductive line of reasoning
going from prediction -> hypothesis -> theory
abduction
- starting from an observation, then guessing what happened (ie. looking at symptoms and figuring out likeliest explanation for them)
- Usually start out with incomplete observations
- Problem because sometimes people have biases that mess up their abductive reasoning -> Ex. focusing on the worst possible potential result (ie. Assuming you have lung cancer instead of stress), or focusing on the potential result that’s the most appealing to you
theory
- overarching framework meant to organize and explain phenomena and data
- Generates hypotheses that test boundaries of the theory
hypothesis
- A tentative statement about variables -> derived from an existing theory
- ex. “People who play violent video games are more aggressive than those who don’t”
data can…
- support hypotheses
- Be (in)consistent with hypotheses
data cannot…
- Confirm hypotheses
- (Dis)prove hypotheses
what makes theories good?
- Supported by data
- Falsifiable
- Parsimonious
falsifiability
- Ability to show a theory to be wrong
- There can exist data that are inconsistent with a theory
- Freud’s ideas were not falsifiable (ex. Oedipus complex -> subconscious, so can’t be proven/disproven)
- Can be considered as a matter of degree
correlational/non-experimental theory
— is related to —
experimental theory
— causes —
what do good hypotheses do?
- Make predictions that expose itself to falsification
- Make specific predictions
what do bad hypotheses do?
- make predictions that are difficult to falsify
- Make general predictions (= weak support)
how does parsimony relate to falsifiability?
- More parsimonious -> more falsifiable
- Fewer conceptual relationships (assumptions) = less data required to counter a theory
- Fewer adjustments to established relationships in science = less data required to test adjustments
- We are evaluating the whole theory
conceptual variable
broad, general, abstract ideas (ex. aggression)
essentialism
- These is an unchanging, underlying essence of an entity that can be defined
- Sense of fixedness
- Ex. “A dog is a dog because it has a dog-ness to it”; there’s nothing you can do to a dog that would make it no longer a dog
- Focus is on the meaning of words
- we don’t use this!!
operationalism
- using operational definitions
- Observable indicator of each variable, used for the purposes of this particular study
- Enable reliable measurement or manipulation of each variable in your hypothesis
- These operational definitions might not be right, but are a place to start
- Ex. How would you operationally define aggression?
literature review
when research is summarized using narrative techniques and without following the typical 6-section format
prediction
- specific prediction about the outcome and operational definitions of particular experiment
- ex. “People who play mortal combat 3 will score higher on the cook-medley hostility scale than people who play my little pony”
5 sources of ideas
- Common assumptions
- Observation of the world around us
- Practical problems
- Theories
- Past research
common assumptions
- Questioning common sense/folk wisdom beliefs (ex. “Do opposites really attract?”)
- Valuable because these assumptions aren’t always correct; the real world is often more complicated than folk wisdom would have us believe
observation of the world around us
- Observing personal or social events (ex. Tipping behaviour in restaurants)
- By viewing the world inquisitively, sometimes we’ll discover things by accident or luck (ex. Pavlov’s discovery of classical conditioning)
practical problems
Experiencing a practical problem can trigger a research project idea (ex. Designing graphic warning labels on cigarette boxes to discourage smoking)
past research
Familiarizing yourself with past research can help generate new ideas for research (ex. Noticing inconsistencies in previous results, alternative explanations that could be explored, etc.)
6 major sections in a research article
- Abstract
- Introduction
- Method
- Results
- Discussion
- References
Abstract
summarizes the entire report
Introduction
explains the problem and the specific hypothesis being tested
method
describes exact procedures used in the study
results
describes the specific findings
discussion
concludes the article by speculating about its broader implications, addressing alternative explanations, discussing why a hypothesis was/was not supported by data, or makes suggestions for further research
references
lists all the sources that were cited in the article (in APA format)
