Chapter 2
● Bias blind spot
○ You believe you don’t think in a biased way
● Meta-analysis
○ Combines the results of many studies and gives a number that
summarizes the magnitude or effect size of a relationship
● Effect size
○ The strength of a relationship between two or more variables
Chapter 3
● Construct validity
○ How well a conceptual variable has been operationalized
● Statistical validity
○ Whether the data of a study supports the claim
● Type 1 error
○ Concluding there’s a relationship between two variables when in fact there
isn’t
● Type 2 error
○ Concluding there’s no association when in fact there is
● Covariance
○ Two variables are related and occur together in situations
● Temporal precedence
○ One variable occurs in time before another
● Face validity
○ Intuitively judge whether measure is good or not
● Content validity
○ Whether all components of the construct appear in the measurement
● Criterion validity
○ Whether the measure is associated with a concrete behavioral outcome it
should be associated with, according to conceptual definition
○ Competitive validity
■ The predictability of a criterion in the present
○ Predictive validity
■ The predictability of a criterion in the future
● Convergent validity
○ Whether constructs meant to be related are in fact related
● Discriminant / divergent validity
○ Whether constructs not meant to be related are in fact unrelated
, Chapter 5
● Ordinal scale
○ Values of quantitative variable are arranged in order
● Interval scale
○ Subsequent numerals represent equal distance but there is no true zero
○ Shoe size / IQ
● Ratio scale
○ Numerals represent equal distances but there is a true zero
○ Number of correct answers
● Internal reliability
○ Consistent data is obtained regardless of how the researcher formulates
question
● Cronbach’s alpha
○ Looks at the relationship between all items
Chapter 6
● Acquiescence
○ Saying ‘yes’ or ‘strongly agree’ to everything as a shortcut
● Fence sitting
○ Choosing middle option so not having/showing an opinion
● Observer bias
○ When researcher’s expectations influence interpretation of participants’
behavior or outcome of study
● Observer / expectancy effect
○ Participant behavior changes to match observer expectations
● Reactivity
○ Change of behavior when participants know they are being watched
Chapter 7
● Probability sampling
○ Every person in a population has equal chance of being selected
● Simple random sampling
○ Listing each individual in a population and randomly selecting some
● Cluster sampling
○ Clusters of participants within a population of interest are randomly
selected, and all individuals from selected clusters are used
● Multistage sampling
○ Two random samples are collected: a random sample of clusters, then a
random sample of people within those clusters
● Bias blind spot
○ You believe you don’t think in a biased way
● Meta-analysis
○ Combines the results of many studies and gives a number that
summarizes the magnitude or effect size of a relationship
● Effect size
○ The strength of a relationship between two or more variables
Chapter 3
● Construct validity
○ How well a conceptual variable has been operationalized
● Statistical validity
○ Whether the data of a study supports the claim
● Type 1 error
○ Concluding there’s a relationship between two variables when in fact there
isn’t
● Type 2 error
○ Concluding there’s no association when in fact there is
● Covariance
○ Two variables are related and occur together in situations
● Temporal precedence
○ One variable occurs in time before another
● Face validity
○ Intuitively judge whether measure is good or not
● Content validity
○ Whether all components of the construct appear in the measurement
● Criterion validity
○ Whether the measure is associated with a concrete behavioral outcome it
should be associated with, according to conceptual definition
○ Competitive validity
■ The predictability of a criterion in the present
○ Predictive validity
■ The predictability of a criterion in the future
● Convergent validity
○ Whether constructs meant to be related are in fact related
● Discriminant / divergent validity
○ Whether constructs not meant to be related are in fact unrelated
, Chapter 5
● Ordinal scale
○ Values of quantitative variable are arranged in order
● Interval scale
○ Subsequent numerals represent equal distance but there is no true zero
○ Shoe size / IQ
● Ratio scale
○ Numerals represent equal distances but there is a true zero
○ Number of correct answers
● Internal reliability
○ Consistent data is obtained regardless of how the researcher formulates
question
● Cronbach’s alpha
○ Looks at the relationship between all items
Chapter 6
● Acquiescence
○ Saying ‘yes’ or ‘strongly agree’ to everything as a shortcut
● Fence sitting
○ Choosing middle option so not having/showing an opinion
● Observer bias
○ When researcher’s expectations influence interpretation of participants’
behavior or outcome of study
● Observer / expectancy effect
○ Participant behavior changes to match observer expectations
● Reactivity
○ Change of behavior when participants know they are being watched
Chapter 7
● Probability sampling
○ Every person in a population has equal chance of being selected
● Simple random sampling
○ Listing each individual in a population and randomly selecting some
● Cluster sampling
○ Clusters of participants within a population of interest are randomly
selected, and all individuals from selected clusters are used
● Multistage sampling
○ Two random samples are collected: a random sample of clusters, then a
random sample of people within those clusters
