Unit 0: Research Design - AP Psychology

hypothesis

tentative explanation; able to be supported to rejected

operational definition

clear, precise, quantifiable definition of your variables—allows replication and collection of reliable data

qualitative data

descriptive data

quantitative data

numerical data—ideal and necessary for statistics

population

everyone the research could apply to

sample

the people (or person) specifically chosen for your study

correlation

identify relationship between two variables

advantage of correlation

useful when experiments are unethical

disadvantage of correlation

correlation does not equal causation

directionality problem

which direction does the correlation go (depression causes low self-esteem, low self-esteem causes depression, or a third variable?)

positive correlation

variables increase and decrease together

negative correlation

as one variable increases, the other decreases

stronger relationships

tighter clusters on graph

experiments

purposefully manipulative variables to determine cause/effect

advantage of experiment

only type that establishes cause and effect

disadvantage of experiment

can be unethical, too artificial

independent variable

purposefully altered by researcher to look for effect

experimental group

received the treatment; can have multiple of these groups

control group

placebo, baseline, can only have one group

dependent variable

measured variable (changes)

placebo effect

any observed effect on a behavior that is “caused” by the placebo

double-blind study

experiment where neither the participant or the experimenter are aware of which condition people are assigned to

single-blind study

only participant blind—used if experimenter can’t be blind

confound/confounding variable

error/flaw in study that is accidentally introduced

random assignment

assigns participants to either control or experimental group at random—increase chance of equal representation among groups (allows you to say cause/effect)

naturalistic observation

observe people in the natural settings

advantage of naturalistic observation

real world validity

disadvantage of naturalistic observation

no cause and effect

case study

studies ONE person (usually) in detail

advantage of case study

collects lots of information

disadvantage of case study

no cause/effect

meta-analysis

combines multiple studies to increase sample size and examine effect sizes

descriptive stats

show shape of the data

measures of central tendency

mean, median, mode

mean

average (use in normal distribution)

median

middle number (use in skewed distribution)

mode

number that occurs most often

bimodal

has two modes—usually indicates good/bad scores

skews

created by outliers

negative skew

mean is to the left

positive skew

mean is to the right

range

distance by smallest and biggest number

standard deviation

average amount the scores are spread from the mean (bigger the number = more spread)

inferental statistics

used to draw conclusions and make inferences after analyzing data collected in surveys; include hypothesis tests and estimation to make comparisons and predictions and draw conclusions that will serve populations based on sample data

statisitical significance

results not due to chance

p<.05 = statistically significant, smaller = better

effect size

data has practical significance—bigger=better

confidentiality

names kept secret

informed consent

must agree to be part of study

informed assent

minors AND their parents must agree

debriefing

must be told the true purpose of the study (done after the deception)

other ethical guidelines

deception must be warranted

no harm against mental/physical health

surveys

usually turned into correlation; subject to self report bias

self report bias

the potential inaccuracy in survey responses due to participants' subjective perceptions or willingness to provide honest answers

social desirability

people lie to look good

wording effects

how you frame the question can impact your answers

random sample (selection)

method for choosing participants for your study—everyone has a chance to take part, increases generalizability

random sample vs. random assignment

sample = generalize; how you select individuals from the population to participate in your study

assignment = cause/effect; how you place those participants into groups

representative sample

sample mimics the general population

convenience sample

select participants on availability—less representative and less generalizability this way

sampling bias

sample is not representative due to convenient sampling

cultural norms

behaviors of a particular group can influence research results

experimenter bias/participant bias

experimenter/participant expectations influences the outcome

cognitive bias

bias in thinking/judgment

confirmation bias

find information that supports our preexisting beliefs

hindsight bias

“I knew it all along”

overconfidence

overestimate our knowledge/abilities

hawthorne effect

people change behavior when watched

what does research need?

peer review and adequate sample sizes