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Conceptual definition
Definition of a variable at a theoretical level
operational definition
how a researcher wants to measure or manipulate a conceptual variable
categorical variables
variables with categories as levels, normally just qualitative, if they contain numbers they have no numerical meaning
quantitative variables
variables with meaningful numbers representing amount or degree
ordinal scale
numbers represent ranked order, intervals are not necessarily equal
interval scale
numerals represent equal intervals between levels and have no true zero
ratio scale
numerals have equal intervals and a true zero (none of the variable is present)
reliability
consistency of results across time or observers
validity
whether the measurement actually assesses what it intends to meaurete
test-retest reliability
consistency of scores each time the same test is administered
interrater reliability
consistency of scores across different observers
internal reliability
consistency of responses across multiple items measuring the same construct
cronbach’s alpha
a coefficient combining inter-item correlations; closer to 1.0 indicates higher internal reliability
average inter-item correlation
average correlation among items, 0.15-0.5 indicates good consistency
face validity
measure appears to assess the intended variable on the surface
content validity
measure captures all parts of a defined cosntruct
criterion validity
extent to which a measure is related to an outcome it should be related tosc
known groups paradigm
scores on the measure differ among groups known to vary on the variable of interest co
convergent validity
measure correlates strongly with measures of similar constructs
discriminant validity
measure does not correlate strongly with measures of different constructs
forced choice questions
respondents pick the best of two or more optionsl
likert scale
degree of agreement scale with labeled response values
semantic differential format
numerical scale anchored with adjectives
open-ended questions,
allow respondents to answer freely; rich but time consuming to code
leading question
wording influences respondents toward a particular answer
double-barreled questions
contain two questions in one, confusing interpretation
negatively worded questions
include negative phrasing that can confuse respondents
question order effects
earlier questions can affect responses to later ones
response sets
tendency to answer all the questions the same way
acquiescence
agreeing with every item instead of responding thoughtfully f
fence sitting
choosing middle or neutral options to avoid extremes
socially desirable responding
giving answers that make oneself look good
faking bad
providing answers that make oneself look worse
flashbulb memories
vivid but often inaccurate memories of significant events
observer bias
observers’ expectations influence their interpretation of behaviors
observer effects
observers unintentionally affect participant behavior
reactivity
participants alter behavior when they know they are being observed
codebook
detailed guide for observers on how to code behaviors
masked design
observers are unaware of study hypothesis or participant conditions
interview
structured conversation to learn participants perspectives
focus group
group interview (6-10 people) discussing a shared experience or topic
external validity
extent to which results generalize to populations beyond the sample
population
entire group of interest
sample
subset of the population studied
census
studying an entire population
population of interest
specific population relevant to the research question
biased sample
sample that excludes some population members systematically
unbiased sample
sample where every member has an equal chance of inclusion
convenience sampling
using participants who are easiest to access
self-selection
participants volunteer themselves, often leading to bias
probability sampling
random methods ensure all members have equal chances
simple random sampling
completely random selection from the population sy
systematic sampling
selecting every nth member after a random start
cluster sampling
randomly select clusters and include all individuals within them
multistage sampling
randomly select clusters, then individuals within those clusters
stratified random sampling
randomly sample within identified demographic groups
oversampling
intentionally overrepresenting certain groups
weighting
adjusting data to correct for underrepresented groups
purposive sampling
selecting specific individuals with certain characteristics
snowball sampling
participants recruit acquaintances
quota sampling
selecting a target number for each subgroup nonrandomly
frequency claims
claims about how often something occurs; rely heavily on external validity
sample size
affects statistical validity more than external validity
association claim
describes a relationship between two measured variables
bivariate correlation
association involving exactly two variables
scatterplot
graph used to visualize relationships between two quantitative variables
bar graph
graph used when one variable is categorical; shows mean differences
effect size
magnitude of a relationship between variables
outlier
extreme score differing greatly from others in the sample
restriction of range
lack of full score range that can weaken correlations
curvilinear association
nonlinear relationship between two variables
covariance
two variables are related (first condition for causation)
temporal precedence
cause precedes effect (second condition for causation)
directionality problem
uncertainty about which variable causes which
internal validity
no alternative explanations (third condition for causation)
third-variable problem
hidden variable explaining the observed relationship between
spurious association
apparent correlation due to subgroup differences
moderator
variable that changes the strength or direction of an association