front 1 What are three (do not use “research is better than experience” as a
reason) reasons not to rely on your own experience as a source of knowledge? | back 1 - Experiences has no comparison group
- experience is
confounded
- research is probalistic
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| back 2 Something that would potentially vary but has one level in the study
in question
ex. Male, happy place, college students |
front 3 Constuct/conceptual varibles | back 3 - Name of concept being studied
- stated at an
abstract/conversational level
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| back 4 - Careful, theoretical definition of the construct
- similar to a tile page
- ex. “A persons cognitive
evaluation of their life”
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front 5 Operational definition/variable | back 5 - How the construct is measured or manipulated in a study
- ex. Hunger: measure blood levels before and after eating
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| back 6 Turn it into a measured or manipulated variable |
| back 7 An argument someone is trying to make |
front 8
When should we, and when should we not trust authorities on a subject? | back 8 - We should trust the authorities on a subject based on the
source of the ideas they are proposing. This can also be if their
research could be based on their research.
- We should not
trust authorities if they base their research on their experience
and intuition. And if they do not have valid research supporting
what they are proposing.
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| back 9 - important for psychology class (know how to become a producer
of research)
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| back 10 - when reading printed or online news stories based on
research
- evaluate real or fake research articles
- critical to future career
- need to know how to
interpret research data with a critical eye
- need to know
the research behind evidence-based treatments
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front 11
What are several reasons not to rely on intuition as a source
of knowledge? | back 11 - you can be swayed by a good story
-
persuaded by what easily comes to mind --> availability
heuristic: states that things that pop up easily in our mind,
tend to guide our thinking
-
you fail to think about what you cannot see
-
focusing on the evidence we like best --> confirmation
bias: looking at the information we want to believe
-
biased about being biased --> Individuals
have
“bias-blindspot”; the belief that we are unlikely to fall
prey to other biases
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| back 12 - is how the construct/concept of interest can turn it into
measured or manipulated as a variable in a study
- example: The variable is hunger so you would have to measure
the blood levels of individuals before and after they eat. On a
scale of 1-5 rate how happy you are today
|
| back 13 - is information that is gathered (observed) and recorded
- variable in a study whose levels (values) are observed or
recorded
- similar to dependent variable
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| back 14 - is controlled by the researcher and assigned at different
levels
- This can be assigning participants to different
levels and values
- similar to independent variable
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| back 15 - something that varies and has 2 levels (values)
- e.g. gender, age, happiness
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| back 16 - frequency claims
- association claims
- causeual
claim
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| back 17 - describes a particular level or degree of a single
variable
-
example: 75% of the world smiled today
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| back 18 - argues that one variable is likely to be associated with a
particular level of another variable, variables that are associated
are said to correlate or convey (when one variable changes, the
other variable tends to change too)
-
example: A late dinner is not linked to childhood
obesity, Students who do retrieval study will do better on exams,
countries with more butter have happier citizens
- positive, negative and zero correlation
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| back 19 - argues that one variable causes a change in another variable,
arguing that a specific change in one variable is responsible for
influencing the value of another variable
example: Pretending to be Batman helps kids stay on task |
front 20
Explain the four ways we validate each of the three types of
claims | back 20 - Construct Validity
- External Validity
- Statistical validity
- Internal Validity
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| back 21 - How well the variables in the study are measured or
manipulated? To the extent which operational variables in a study
are a good approximation of conceptual variables
- how
good a study is extensionally is
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| back 22 - the extent to which results of a study are generalized to some
larger population & other times or situations
- how
it relates to the real world rather in a controlled environment
such as a lab
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| back 23 - How well the numbers support the claim, can the study be
replicated, or is it due to change, the extend in which statistical
conclusions derived from a study are accurate and reasonable
- how the statistics support the study and how it relates to
the claim
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| back 24 - is there another variable that could account for the results,
is a study’s ability to rule out alternative explanations for a
causal relationship between 2 variables
- seeing if an
outside variable has an effect on the overall study and taking it
into account
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front 25
Explain and identify the three criteria for causation. | back 25 - covariance
- temporal precedence
- internal
validity
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| back 26 - study shows that as A changes, B changes
- the degree to
which 2 variables go together
- e.g. high levels of A go
with high levels of B
- e.g. Halloween (↑) causes candy
(↑)
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| back 27 - study’s method ensures that A comes first in time before B
- causal variable comes first before the effect variable
(time)(precedence)
- proposed causal variable comes first in
time before the proposed outcome variable
- e.g.
Halloween (1st) causes candy (2nd)
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front 28 internal validity (for causation) | back 28 - study’s method ensures that there are no plausible alternative
explanations for the change in B; A is the only thing that
changed
- ability to rule out an alternative explanation for
the variable
- e.g. Fre❌ddies cause candy
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front 29
Distinguish between conceptual and operational definitions.
Understand why operationalization is so important. | back 29 -
conceptual definition: a researcher’s definition of
a variable at the theoretical level, which can be called
construct
-
operational definition: how the construct/concept
of interest can turn it into measured or manipulated as a variable
in a study
- operationalization is important because it is
the process of turning a construct of interest into a measured or
manipulated variable
|
front 30
Explain the three common types of measures – self-report,
observational, and physiological measures. Give examples and/or
identify each. | back 30 -
self-report: operationalize a variable by recording
people’s answers to questions about themselves in a questionnaire or
interview
- Self-reports for children can be done on
parents or teacher reports
- e.g. Diener’s five-item scale
or ladder of life
-
observational measures: (behavior measure) a
measuring a variable by operationalizes observable behaviors or
physical traces of behaviors
- e.g operationalize
happiness by observing how many times a person smiled
-
physiological measures: operationalize a variable
by recording biological data; may require the use of equipment to
measure data
- e.g. can be brain activity, hormones
levels, or heart rates (FMRI)
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front 31
Explain and identify the different scales of measurement –
categorical, ordinal, and interval/ratio scales. | back 31 -
categorical: levels are categories
- e.g. sex whose levels are female and male
-
ordinal scale: measurement applies when the numeral
of a quantitative variable represents ranked order, in which levels
are not equal
- e.g. bookstore’s website might display
the top 10 best-selling books
-
interval/ratio: measurement applies to the numerals
of a quantitative variable that meets 2 conditions; (1) numerals
represent equal intervals (distances) between levels, and (2) there
is no “true zero”
- E.g. IQ test with the distance of
scores of 100 & 105 is similar to 105 & 110
|
front 32
Explain and identify face and content validity | back 32 - face validity: the measure has this if it is subjectively
considered to be a plausible operationalization of the conceptual
variable in question
- content validity: a measure must
capture all parts of a defined construct
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front 33
Explain and identify criterion validity | back 33 an empirical form that evaluates whether the measure under
consideration is associated with a concrete behavioral outcome that it
should be associated with, according to the conceptual definitions |
front 34 Explain and identify convergent and discriminant validity. | back 34 -
Convergent validity: an empirical test of the
extent to which a self-report measure correlates with other
measurements of theoretically similar conduct
-
discriminant validity: an empirical test of the
extent to which a self-report measure does not correlate strongly
with measures of theoretical dissimilar constructs
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front 35 Why is PsycINFO your best source of research? | back 35 - The best source of research
- It also has
advantages such as showing articles made by the same author and if
the sources are peer-reviewed.
- a comprehensive tool for
sorting through vast amounts of psychological research
- Searches sources only in psychology and reputable
sources
- Everything about psychology is in there,
always use it
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front 36 Know the difference between a measured and a manipulated variable,
and be able to identify both. | back 36 - A measured variable is information that is gathered (observed)
and recorded
- variable in a study whose levels (values)
are observed or recorded
- similarly to the dependent
variable
- Manipulated variable is controlled by the
researcher and assigned at different levels
- This can
be assigning participants to different levels and values
- similar to the independent variable
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front 37
Define and create operational definitions | back 37 - Operational Definition is how the construct/concept of interest
can turn it into measured or manipulated as a variable in a
study
- example: The variable is hunger so you would have
to measure the blood levels of individuals before and after they
eat. On a scale of 1-5 rate how happy you are today
|
front 38
Explain and identify the three types of reliability –
test-retest, interrater, and internal consistency. | back 38 -
test-retest reliability: consistency in results
every time a measure is used
- e.g. IQ test and
personality
-
interrater reliability: the degree in which 2 or
more coders or observers give consistent ratings of a set of
targets
-
internal consistency: in a measure that contains
several items. the consistency in a pattern of answers, no matter
how a question is phrased, consistent scores are obtained no matter
who measures the variable
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front 39
What are the features of good scientific theories? | back 39 - (1) Theory; a statement or a set of statements
that describes general principles about how variables relate to one
another
- (2) hypothesis; a statement of the
specific result the researcher expects to observe from the
particular study if the theory is accurate
- (3)
Data; is a set of observations representing the values of
some variables collected from one or more research studies
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front 40
Describe the theory-data cycle | back 40 - the theory leads researchers to propose
particular research questions → research questions;
- which
leads to an appropriate → research design; to test
specific hypnosis (non-supporting data leads to revised theories or
improved research design);
- the hypothesis
is ideally pre-registered before you collect and analyze → data;
which feeds back into the cycle (→ supports data to strengthen
theory)
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front 41
Why don’t theories prove anything? | back 41 - The word, “prove”, is not used in science, instead of saying
“prove,” scientists say that a study's data supports or is
consistent with theory.
- If a hypothesis is not
supported, scientists might say data is inconsistent with the
theory (a single confirming finding can not prove a theory)
(scientist may troubleshoot the study instead of rejecting the
theory)
|