Chapter 5 Flashcards
Self-report measures
recording people’s answers to questions about themselves in a questionnaire or interview
Observational measures
recording observable behaviors
Physiological measures
operationalize a variable by recording biological data (e.g., brain activity, hormonal levels, heart rate
Categorical variables
their levels are qualitatively distinct categories; for example, species (rhesus macaque, bonobo, chimpanzee)
Quantitative variables
variables coded with meaningful numbers; for example, height, weight, or scale of subjective well-being.
Ordinal scale
Ranked order (first, second, third places in a race—first place isn’t twice as fast as second place).
Interval scale
Numerals represent equal distances between levels and there is no true zero (zero does not mean “nothing”); for example, IQ score (a score of 160 is twice as large as a score of 80).
Ratio scale
Numerals represent equal intervals and there is a true zero, for example, height or exam scores.
Reliability
how consistent the results of a measure are
Test-retest reliability
: Consistent scores every time the measure is used; for example, give an IQ test at Time 1 (T1), at the beginning of the semester, and again at Time 2 (T2), at the end of the semester. The scores should be relatively consistent across the two times.
Interrater reliability
Consistent scores no matter who does the measuring; for example, two observers measure how often a child smiles during one hour at a daycare playground, and their counts are consistent with one another.
Internal reliability (aka internal consistency
A participant provides a consistent pattern of responses, regardless of how the researcher has phrased the question; for example, a researcher asks in several different ways about how lonely you feel, and your responses are consistent with one another.
Correlation coefficient
a single number that describes how close the dots on a scatterplot are to the line drawn through them
Strength
When dots are close to the line, you have a strong relationship. When dots are spread out, you have a weak relationship
Validity
Whether the operationalization is measuring what it’s supposed to measure.
Deception
two types of deception—omission (withholding details of the study from participants) and commission (lying to participants).
Debriefing
When researchers use deception, they need to debrief participants following their participation. Debriefing sessions are typically conducted verbally, and the researcher explains why deception was used and the nature of the deception.
Data fabrication
researchers invent data that fit their hypotheses
Data falsification
researchers selectively delete observations or influence participants to act in a particular way
criterion validity
whether the measure is related to a concrete outcome that it should be related to
Convergent validity
A measure should correlate strongly with other measures of the same construction
Discriminant validity aka divergent validity
A measure should correlate less strongly with measures of different constructs; in other words, there must be differences
