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evolutionary perspective
survival of the fittest (hereditary)
psychoanalytic perspective
unconscious motives
childhood events
cognitive perspective
thinking, perceptions, memory, interpretations, mind
behavioral perspective
learning & conditioning
reinforcement
humanistic perspective
reach potential
acceptance, growth, & love
biological perspective
born with it
neurotransmitters, hormones, nervous system
critical thinking
examines assumptions, appraises the source, finds biases, & evaluates evidence
hindsight bias
“i knew it all along”
overconfidence
we always think that we are right
“i was so close”
confirmation bias
we look for statistics & facts that support the beliefs that we already have
illusory correlation
perceiving a relationship where none exists or perceiving a stronger than the actual relationship (random coincidence)
null hypothesis
states no relationship exists between the two variables being studied
is the statement that a researcher or an investigator wants to disprove
testing can tell you whether your results are due to the effects of manipulating the dependent variable or due to random chance
falsifiable
“can it be proven wrong?”
ensures that hypotheses can be tested & potentially refuted
operational definitions
defines what the researcher will be observing & manipulating
generalized
measurable and manageable
used to replicate the study
case study
give an in-depth investigation of an individual or group
naturalistic observation
observing behavior in its natural setting
social-desirability bias
wanting to look good
when respondants give answers that they think are socially acceptable rather than truthful
self-report bias
flawed memories
when participants provide inaccurate info about themselves
sampling bias
skewed selection
when the sample is not representative of the population
leads to unrepresentative & unreliable results
wording effects
how you frame the question
how the researcher words questions
population
the entire group that a researcher is interested in studying
random sample
anyone you pull for the study
reduces bias & increases representativeness
representative sample
smaller sample that represents the population
gets rid of confounding variables in a population
convenience sampling
easy, but risky
selecting participants who are readily available
may not represent the broader population
correlation
a relationship between 2 variables
answers “how well does A predict B?”
correlation does not equal causation
directionality problem
you don’t know what variable causes the other
third variable problem
an undiscovered causitive variable
another that can influence the 2 variables studied in a correlational study
regression towards the mean
the tendency of outliers to be followed by data points that are closer to the mean