PSY-2150 Final: Terms Study Guide Part 2
4 Feb 2020
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Words to Describe Variables
• Types of variables
• Qualitative (properties that differ in kind/type) and quantitative variables (properties that
differ in amount)
• Note that both can produce numerical data (ex. you can count how many/percentage
in each category)
• Discrete (no intermediate values possible between adjacent values) and continuous
variables (intermediate values possible)
• Independent (presumed cause, manipulated in experiment) and dependent variables
(presumed effect)
• Hypothetical constructs--underlying characteristics or processes that are not directly
observed but instead are inferred from measurable behaviors or outcomes
• Mediator (variable that provides a causal link in the sequence between an independent
variable and a dependent variable; ex. distraction of attention is link between cell phone use
while driving and impaired driving performance) and moderator (a factor that alters the
strength or direction of the relation between an independent and dependent variable; ex. in
cell phone and driving example, talking in high traffic density and talking in low traffic
density) variables
• Other types of variables
• Situational variable--characteristic that differs across environments or stimuli
• Subject variable--personal characteristic that differs across individuals
• Defining variables
• Conceptual definitions
• Operational definitions--defining a variable in terms of the procedures used to measure or
manipulate it
• Measurement--process of systematically assigning values to represent attributes of organisms,
objects, or events
• Scales of measurement (rules for assigning scale values to measurements)
• Nominal--the scale values represent only qualitative differences; numbers can be assigned
to the categories (ex. male=1 and female=2) but these are arbitrary numbers; you can
however count how many in each category and perform statistical procedures with this (ex.
percentage of male and female participants)
• Ordinal--different scale values represent relative differences in the amount of some
attribute (think ranking, even things like top priority, priority, and low priority represent
ordinal scaling)
• Interval--equal distances between values on the scale reflect equal differences in the
amount of the attribute being measured
• Ratio--equal distances between values on the scale reflect equal differences in the amount
of the attribute being measured and the scale also has a true zero point
• Criterion variable--the variable we are trying to estimate or predict
• Predictor variable--the variable whose scores are used to estimate scores of a criterion variable
Words to Describe Sampling
• Population--all cases of interest to us
• Sample--subset from population
• Sampling frame--a list from which a sample will be selected
• Representative sample--reflects important characteristics of population
• Nonrepresentative sample--does not
• Response rate--those who participate divided by all those selected
• Social desirability bias--respond in way you think is expected rather than the way you feel you
want to
• Probability sampling--each member of the population has a chance of being selected into the
sample and the probability of being selected can be specified
• Simple random sample--all in sampling frame have equal probability to participate
• Stratified random sampling--a sampling frame is divided into groups and then within each
group, random sampling is used to select the members of the sample
• Cluster sampling--units that contain members of the population are identified. These units
are then randomly sampled
• Single-stage cluster sampling--all the participants in the randomly selected clusters are
chosen to participate in the survey
• Multistage sampling--the use of two or more stages to select progressively smaller samples
• Nonprobability sampling--each member of the population either does not have a chance of being
selected into the sample, the probability of being selected cannot be determined, or both
• Convenience sampling --members of a population are selected non-randomly for inclusion in
a sample on the basis of convenience
• Quota sampling--a sample is non-randomly selected to match the proportion of one or more
key characteristics of the population
• Self-selection--occurs when participants place themselves in a sample rather than being
selected for inclusion by a researcher
• Purposive sampling--researchers select a sample according to a specific goal or purpose of
the study, rather than at random
• Expert sampling--researchers identify experts on a topic and ask them to participate
• Snowball sampling--people contacted to participate in a survey are asked to recruit or
provide contact information for other people who meet the criteria for survey inclusion
• Sampling variability--chance fluctuations in the characteristics of samples that occur when we
randomly select samples from a population
• Margin of sampling error--a range of values within which the true population value is presumed to
reside
• Confidence level--a degree of confidence that the true population value resides within a particular
margin of error
Words to Describe Measurement
• Measurement accuracy, reliability, and validity
• Accuracy--represents the degree to which the measure yields results that agree with a
known standard
• Systematic error--a consistent degree of error that occurs with each measurement
• Reliability--assessed by examining consistency (precision)
• Random measurement error--random fluctuations that occur during measurement
and cause the obtained scores to deviate from a true score
• Ways to measure reliability
• Test-retest reliability--determined by administering the same measure to the
same participants on two or more occasions, under equivalent test conditions
• Split-half reliability--examines how strongly scores on two halves of a test
correlate
• Interrater reliability--examines how well the coding, ratings, or other
observations of two or more independent observers agree
• Validity--the degree to which we can truthfully infer that a measure actually does what it is
claimed to do (looks at the purpose/goal of the measure)
• **For a measure to be valid, it must first be reliable (reliability is a necessary but
insufficient condition for validity)
• Face validity--concerns the degree to which the items on a measure appear to be
reliable
• Content validity--does the content of a measure adequately represent the range of
relevant content; the degree to which the items on a measure adequately represent
the entire range or set of items that could have been appropriately included
• Construct validity--does a measure assess the construct that it is claimed to assess and
not some other construct?
• Convergent validity--scores on a measure should correlate highly with scores on
other measures of the same construct
• Discriminant validity--scores on a measure should not correlate too highly, if at
all, with measures of other constructs
• Criterion validity--do scores on a measure relate to scores on a relevant criterion;
addresses the relation between scores on a measure and an outcome/how well a
measure can predict or estimate a criterion
• Predictive validity--scores on a measure should help us predict future scores on
a criterion
• Concurrent validity--scores on a measures should help us estimate current
scores on a criterion
Words to Describe Ethical Research
• The ethics code:
• Beneficence--strive to benefit those with whom they work
• Nonmaleficence--do no harm
• Fidelity--behave in a trustworthy manner
• Responsibility--adhering to professional codes of conduct
• Integrity--be honest and truthful
• Justice--benefits should be made available to all
• Respect--dignity and worth of all people
• Informed consent and assent (if cannot fully comprehend details of study)
• Deception--intentionally withholding information/mislead participants
• Coercion
EXPERIMENTAL DESIGNS
Single-Factor Experimental Designs (Chapter 8)
• Single-factor design--has only one independent variable; this independent variable must have at
least 2 conditions/levels [multi-level designs are usually more accurate because you can examine
more; linear to nonlinear in some cases, more revealing]
• Experimental condition--exposing participants to a treatment or "active" level of independent
variable
• Control condition--participants do not receive treatment or are exposed to a baseline level of the
independent variable
• Between-subjects designs--each participant engages in only one condition
Document Summary
Situational variable--characteristic that differs across environments or stimuli. Sampling frame--a list from which a sample will be selected: population--all cases of interest to us, representative sample--reflects important characteristics of population, nonrepresentative sample--does not, response rate--those who participate divided by all those selected. Simple random sample--all in sampling frame have equal probability to participate. Stratified random sampling--a sampling frame is divided into groups and then within each group, random sampling is used to select the members of the sample: cluster sampling--units that contain members of the population are identified. Snowball sampling--people contacted to participate in a survey are asked to recruit or provide contact information for other people who meet the criteria for survey inclusion. Words to describe measurement: measurement accuracy, reliability, and validity, accuracy--represents the degree to which the measure yields results that agree with a known standard. Split-half reliability--examines how strongly scores on two halves of a test correlate. Words to describe ethical research: the ethics code:
