Chapter 1 Topics 3 and 4 Flashcards
descriptive research
- seeks to explain how an individual behaves, esp. in natural environments
- some examples include case studies, naturalistic observation, and surveys
descriptive research
case studies
descriptive research that involves intensive examination of an “atypical” person
descriptive research naturalistic observation
- observing people/animals in their natural environment
advantages naturalistic observation
- provides a rich description of behaviour
- can avoid demand characteristics
limits to naturalistic observation
- usually, experimenter cannot inform a person that they are being observed (can’t ask participants to perform a task, how they’re feeling, etc. because of demand characteristics)
- requires long periods of observation to get a single measure of a desired behaviour (have to wait and observe for a long time to observe rare behaviour)
Descriptive Research Survey Research
- ask participants questions through interviews or questionnaires
- see people’s views., experiences, traits
Survey limitations
- cannot be used to draw conclusions about cause and effect
- surveys rely on participants self-reports
- incorrect generalizations about populations if sample = unrepresentative
- social desirability bias
Population
- the entire set of individuals about whom we wish to draw a conclusion
Sample
a subset of individuals drawn from a population
Representative Sample
- a sample that reflects the important characteristics of the population
Random Sampling
- every member of the population has an equal probability of being chosen
small representative sample vs larger non-representative sample – which is better
small representative sample even tho bigger sample size is usually better
correlational research
- looking for an association/relationship between 2 or more measured variables
- no manipulation of variables, therefore no causal relationships
- CORRELATION ≠ CAUSATION
correlational research steps
- researcher measures x
- researcher measures y
- are the two variables (x and y) related
pros of correlational research
- shows what we actually find: a relationship
- ex. social relationships and happiness are correlated
- show the strength of present relationships
- can be used to make predictions about variables
- identifies “real-world” associations
cons of correlational research
- can’t show what people actually want: a causal relationship because of bidrectionality
- reminds us that two variables may be related to one another only because they are both causally related to a third variable
- Can’t assume cause-effect relationship exists
- Shows an association NOT a cause
bidirectionality problem
does X cause Y or does Y cause X? Or do both influence each other?
third variable problem
the concept that a correlation between two variables may stem from both being influenced by some third variable
correlation coefficient (r)
- describes the kind of relationship that exists between two variables
- ranges from -1 to +1
- sign indicates direction
- absolute value indicates strength
positive correlation (r)
A correlation where as one variable increases, the other also increases, or as one decreases so does the other. Both variables move in the same direction.
ex. the more cats I have, the happier I feel
negative correlation (r)
as one variable increases, the other decreases
ex. the more work I have, the less happy I am
zero correlations (r)
- there is no relationship.
- the two variables are not correlated with one another.
- as x increases or decreases, y doesn’t change in an orderly fashion
- r=0
- r does not usually equal 0 because of error (r is at least an extremely small value)
