psy: 2811, research methods exam 1 questions and answers 2026-2027(A+ GRADED)

construct validity

how well the variables in a study measure what they intend to measure e.g. measuring intelligence

external validity

the extent to which the results of a study generalize to some larger population e.g. whether the results from a sample of children apply to all U.S schoolchildren

statistical validity

the extent to which statistical conclusions derived from a study are accurate and reasonable. also addresses the extent to which a study minimizes the probabilities of type 1 & 2 errors

internal validity

the validity of the target variable and not some alternate variable; could another factor of the study explain the results? relates to the number of confounds are in the study, e.g. living in the residence halls causes higher social satisfaction with campus experience (confound: year in college?)

confounds

something other than the main manipulated variable, if there is a lot of these your study has low internal validity

type 1 errors

saying an effect exists when it does not; false positive, worst kind of error

type 2 errors

saying no effect exists when there is one; false negative, not as damaging

face validity

it LOOKS like what you want to measure, e.g. IQ tests measure intelligence

content validity

the measure contains all the parts that your theory says it should contain, strict; it DOES measure what it is supposed to. e.g. taking a self-exam about sleep measures your sleep, if it does actually measure your sleep the test has this

criterion validity

your measure is correlated with a relevant outcome; it actually predicts what it is supposed to. e.g. the ACT predicts performance in college

convergent validity

your measure is more strongly associated with measures of similar constructs, e.g. in a measure of self-esteem, a researcher may want to show measures of similar constructs, such as self-worth, confidence, social skills, and self-appraisal which are also related to self-esteem, whereas non-overlapping factors, such as intelligence, should not be measured

discriminant validity

ensures that in the study, the non-overlapping factors do not overlap. e.g. self esteem and intelligence should not relate in most research projects.

test-retest reliability

people get consistent scores every time they take the test

interrater reliability

consistencies between raters. high when the raters are consistent, low when not

internal reliability

people give consistent scores on every item of a questionnaire; how similar peoples responses are, measured with cronbach's alpha

cronbach's alpha

a correlation-based statistic that measures a scale's internal reliability, scale from 0-1, .70 and above is a good score

frequency claims

statements of how common a behavior, occurrence, etc. is e.g. percent of students in class that have twitter accounts

association claims

suggests that there is a link between two variables, does not argue for causality

causal claims

an argument that two variables are related & that one variable causes another. look for direct terminology such as leads to, affects, causes, changes, etc.

operationalization

the process of assigning a precise method for measuring a term being examined for use in a particular study. e.g. in a religion study: asking how often people attend religious services

ordinal scale

represent a rank order, e.g. ranking of 10 movies from most to least favorite

interval scale

subsequent numbers represent equal distances but there is no true zero, e.g. shoe size, IQ score

ratio scale

numbers represent equal distances, but there is a true zero, e.g. number of exam questions answered correctly, height in cm

categorical

e.g. gender, nationality, favorite music

quantitative

variables that use meaningful numbers

measured variable

a variable in an experiment whose levels (values) are observed and recorded

manipulated variable

factor in an experiment that is purposefully changed/tampered with

constant variable

variable that stays the same

five ethical principles: beneficence and nonmaleficene

treat people in ways that benefit them and society, do not cause suffering

five ethical principles: fidelity and responsibility

establish relationships of trust, accept responsibility for professional behavior

five ethical principles: integrity

strive to be accurate, truthful, and honest as a researcher

five ethical principles: justice

treat all people equally, sample research participants from the same populations will benefit from that research (be aware of bias)

five ethical principles: respect for peoples rights and dignity

recognize that people are autonomous & have a right to privacy

empiricism

gaining knowledge through observation and experimentation

theory data cycle

theory, research questions, research design, hypothesis, data

present bias

intuitions influence thinking

cherry picking

act of pointing at individual cases or data that seem to confirm a particular position, while ignoring a significant portion of related cases or data that may contradict that position

confirmation bias

a tendency to search for information that supports our preconceptions and to ignore or distort contradictory evidence, e.g. hating when people bike in the road therefore noticing bikers in the road more often

bias blindspot

thinking you have no bias (reducing bias means knowing you have bias)

implicit bias

unconscious attribution of particular qualities to a member of a certain social group