Final Exam Flashcards
(119 cards)
1
Q
Explain why it’s beneficial to be a critical consumer of information
A
for your future career/evidence-based approach
crucial especially in a world of AI
2
Q
Explain how scientists are empiricists
A
scientists are empiricists because empiricism is the use of verifiable evidence as the basis for conclusions; collecting data systematically and using to develop/ challenge a theory
3
Q
Explain what theory-data cycle is
A
theory –> research questions –> research design –> hypothesis –> data
then have to determine if you need to revise due to nonsupporting data or if data does back up theory = support
4
Q
Explain the features of good scientific theories
A
supported by data
falsifiable
- when tested, can fail to support the theory
have parsimony
- simple > complicated study
don’t prove anything
- theories don’t prove anything, implies no room for error which is not possible
5
Q
Explain the differences between basic vs. translational vs. applied research
A
basic - enhance general body knowledge
transitional - real world problem solved in lab
applied - real-world setting
6
Q
Describe the differences between empirical journals and popular journalism
A
empirical - scientific
popular - broad claims based on research
7
Q
Explain two problems with basing beliefs on our own experience
A
could be biased information
don’t have a comparison group
8
Q
Explain what it means for research to be probabilistic
A
probabilistic - finding are not expected to explain all the cases all the time, there are exceptions
9
Q
Describe at least five ways intuition is biased
A
being swayed by a good story
availability heuristic
- cognitive bias due to recent exposure to topic
present/present bias
- forget to seek information that isn’t there
confirmation bias
- look for information accepting our beliefs, denying info that contradicts beliefs
bias blind spot
- think biases don’t apply to you, failing to notice own cognitive bias
10
Q
Explain whether we should be cautious about accepting the conclusions of authority figures (especially conclusions that are not based on research)
A
could be disinformation
ask if you can cross-check this story and what the context is
it may be politically biased
11
Q
Explain the advantages of research over intuition and experience
A
not influenced by your beliefs
12
Q
Identify variables and distinguish a variable from its levels (or values).
A
variable - thing being studied that varies from person to person
need two levels to each variable
13
Q
Discriminate between measured and manipulated variables
A
measured - observed and recorded
manipulated - controlled
14
Q
Describe a variable both as a conceptual variable and as an operational definition
A
conceptual - not measurable
operational - specific definition/way to measure something
15
Q
Indicate how many variables frequency, association, and causal claims typically involve
A
frequency - one measured variable
association - at least two measured variables
causal - at least two measured variables
16
Q
Describe and identify positive, negative, and zero associations
A
positive - goes low to high
negative - high to low
zero - no definite slope present
17
Q
Identify verbs that signal causal claims versus association claims
A
association:
- is linked to
- is associated with
- is correlated with
- prefers
causal:
- affects
- prevents
- fights
- changes
18
Q
Explain the three criteria used to evaluate a causal claim: covariance, temporal precedence, and internal validity
A
covariance - 2 variables are related
temporal precedence - study conducted showing cause came before effect
internal validity - clarifies that variable B is the only thing to cause/change variable A
19
Q
Understand that very few studies can achieve all four kinds of _______ at once, so researchers must prioritize some over others depending on what kind of claim the researcher is making
A
validity
20
Q
Describe the Tuskegee Syphilis Study and explain how it violates the three ethical principles of the Belmont Report
A
tuskegee - black individuals with syphilis, doctors didn’t tell them what was wrong and left some people without treatment to see what would happen
violated:
respect for person: no informed consent
beneficence: didn’t protect people from harm
justice: targeted black people in specific
21
Q
Explain informed consent and the protection of vulnerable groups (applying the principle of respect for persons)
A
informed consent process:
1. voluntariness
- no coercion
- no undue influence/bias from experimenter
2. information
3. comprehension
- study is easily understandable to participant
22
Q
Explain how researchers might evaluate the risks and benefits of a study (applying the principle of beneficence)
A
confidentiality
privacy
anonymity
debriefing
emphasizing voluntary nature of participation
23
Q
Explain how researchers would apply the principle of justice in selecting research participants
A
make sure you aren’t targeting participants because they are easily accessible
24
Q
Define three forms of research misconduct
A
data fabrication
- made up data to fit hypothesis
data falsification
- removing data that can falsify study
plagiarism
25
Describe what institutional review boards do
review studies to make sure they are ethical/protects participants
26
Describe deception and explain when deception is considered permissible in a study
deception is when you are lying to the participants (commission) or withholding information (omission)
only ok to use if there is a strong reason and participants are debriefed after the study
27
Describe the debriefing process and the goals of debriefing.
to let the participant know what the purpose of the experiment was, how it is going to further the literature and describe their role in it
28
Describe the role of an institutional animal care and use committee (IACUC) and the Animal Welfare Act in protecting the welfare of animals in research
AWA - federal law that regulates treatment in teaching, research, etc., anytime an animal is included
IACUC - institutional level, need approval from this committee before study is published involving animals
29
Explain the animal care guidelines and the four R’s
replacement
- find alternative if possible instead of animals
refinement
- altering research procedures to reduce stress
reduction
- fewest number of animals possible
rehabilitation
- caring for animal after experiment ends
30
Recognize the difference between a conceptual variable and its operationalization
conceptual - construct or theoretical
operational - how it's measured or manipulated
31
List three ways psychologists typically operationalize variables
self-report, observational, and physiological
32
Classify/identify measurement scales as categorical or quantitative; further classify quantitative variables as ratio, interval, and ordinal
categorical - things/cannot be represented with numbers
quantitative - nominal
ratio - true 0, = distance between numbers
interval - no true 0, = distance between numbers
ordinal - ranking/order, not = distance between numbers
33
Describe the difference between the validity and the reliability of a measure
reliability - measure
validity - accuracy
a test can be reliable but not valid, but a valid test has to be reliable
34
Identify three types of reliability (test-retest, interrater, and internal), and explain when each type is relevant
test-retest: whether the numbers stay the same or change overtime
interrater: degree to which observers agree in measurement of behavior
internal: each item in test is measuring same underlying construct, only apply to a scale with multiple items
35
Review scatterplots, focusing on how scatterplots show the direction and strength of a relationship
same as correlation
36
Apply the correlation coefficient, r, as a way to describe the direction and strength of a relationship
strong = high or low
positive = positive slope
negative = negative slope
37
Explain what face, content, criterion, convergent, and discriminant validities are
face - it looks like what you want to measure
content - the measure contains all the parts that your theory says it should contain
criterion - predictive validity
convergent - scores on the measure are related to other measures that are theoretically similar
divergent - scores on the measure are related to other measures that are theoretically different
38
Describe how scatterplots, r, and known groups can be used to evaluate validity
known groups - giving measure to group known to have condition/traits/outcome to have a reliable outcome
39
Describe the different ways questions can be worded: open-ended, forced-choice, and using rating scales
open - lots of information but hard to analyze/compare
forced - providing options that participants have to chose from, limited information
likert - anchored by terms like not at all and totally
semantic differential format - scale anchored by adjectives
40
Explain how to increase the construct validity of questions by wording them carefully and by avoiding ...
leading, double barreled, and negatively worded questions hurt construct validity
41
Explain how question order can change the meaning/validity of a question
can give away the answer the researcher is looking for
42
Explain ways to increase the construct validity of questions by preventing respondent shortcuts/response sets (such as ...), biases (such as ...), or simple inability to report
shortcuts: acquiescence (yea-saying) and fence-sitting (choosing middle/neutral option)
biases: socially desirable responding/faking good, faking bad
43
Explain the strengths of respondent’s reports/informants’ reports
self reports strengths:
- people are their own best expert
- access to thoughts, feelings, and intentions
- definitional truth: whatever they say goes
- cost effective
44
Explain the weaknesses of respondent’s reports/informants’ reports
self reporting more than they know
self reporting memories of events
carelessness
rating products
bias
45
Explain ways to improve the construct validity of observations by reducing ...
observer bias, observer effects, and target reactivity
46
solutions for reactivity
blend in
wait it out
measure the behavior's result
47
Explain the difference between population of interest and samples
population of interest - whole target population
sample - small portion of target population
48
Define sampling problems that lead to biased samples
convenience sampling
- researchers sample easiest ppl to recruit
self selection
- sampling only those who volunteer to participate
49
Explain why a random sample is more likely to be a representative sample and why representative samples have external validity to a particular population
give everyone in the population of interest a chance to be sampled, easier to generalize = higher external validity
50
Explain techniques for random sampling: simple random sampling, cluster sampling, multi-stage sampling, stratified random sampling, oversampling, and systematic sampling
simple random
- random picking of all people in population of interest
cluster
- groups of people but are arbitrary
multi-stage
- random selecting from clusters, not using everyone in each cluster like cluster sampling
stratified
- groups are created specifically to represent population of interest
oversampling
- like stratified but overrepresent groups on purpose
systematic
- random select starting point and interval you select people in
51
Describe techniques of nonrandom sampling: convenience sampling, purposive sampling, snowball sampling, and quota sampling
convenience
- internal validity > external
purposive
- use specific type of person/study a specific group, biased recruiting
snowball
- asking participants to recommend other people they know that the study is observing
quota
- set target number of recruitment until quota is met
52
Explain why it is more important, when assessing external validity, to ask how a sample was collected rather than how large it is
more generalizable if it was a random sample than if it had a ton of people
53
Estimate results from a correlational study with two quantitative variables by looking at a scatterplot.
yup
54
Understand how the correlation coefficient, r, represents the _______ and ________ of a relationship between two quantitative variables, and how to apply Cohen’s guidelines for evaluating strength of association
strength; direction
small: more than 0.10
moderate: more than 0.30
large: more than 0.50
55
Interpret data from a correlations table
don't compare beta's from different tables!
56
Analyze a correlational study, in which at least one variable is categorical by looking at a bar graph and computing the difference between the two means
yup
57
Interrogate the construct validity of an association claim, asking whether the measurement of each variable was _____ and _____
reliable; valid
58
Interrogate the statistical validity of an association claim, asking about features of the data that might distort the meaning of the correlation coefficient, such as outliers in the scatterplot, effect size, and the possibility of restricted range as well as whether the correlation is statistically significant. When the correlation coefficient is zero, inspect the scatterplot to see if the relationship is curvilinear
got it
59
Interrogate the external validity of an association claim by asking __ _____ the association can generalize
to whom
60
Distinguish an association claim, which requires that ... , from a causal claim, which requires that the study ...
a study meets only one of the three rules for causation (covariance);
also establish temporal precedence and internal validity
61
Explain how longitudinal designs are conducted
measured over time with same participants
62
Identify three types of correlations in a longitudinal correlational design: cross-sectional correlations, autocorrelations, and cross-lag correlations
cross-sectional
- relationship between 2 variables at one point in time
auto
- looking at correlation of each variable of itself across each time point
cross-lag
- correlation between one variable and another time point
- only one close to establishing temporal precedence
63
Interpret different possible outcomes in cross-lag correlations, and make a causal inference suggested by each pattern
if both are significant they are neutrally reinforcing, don't know which is causing which
64
Explain how multiple-regression designs are conducted
add multiple variables to the study to control for confounds and compare beta's/strength of correlation
65
Identify and define dependent (criterion) variables and independent (predictor) variables in the
context of multiple-regression data
criterion
- main IV that you are comparing other IV's too
predictor
- third variables that you are controlling for
66
Identify and interpret data from a multiple-regression table and explain, in a sentence, what each coefficient means
beta is used to compare strength while the P value is used to show significance
67
Explain why experiments are superior to multiple-regression designs for controlling for third variables
allows the experimenter to randomly assign people to a group which increases internal validity
68
Explain the value of pattern and parsimony in research
easier to replicate/verify in future studies as the simpler and easier the pattern is, the better!
69
Articulate the difference between mediators, third variables, and moderating variables
mediators
- ask "why", explaining process in which something happens
third variables
- external to the study, problematic
moderators
- ask "for whom" or "when"
70
Distinguish measured from manipulated variables in a study
measured
- observed and recorded
- DV
manipulated
- researcher has an influence/impact on results of participants IV
71
Identify an experiment’s independent, dependent, and control variables
IV
- manipulated
DV
- measured, outcome variable
control
- any variable that an experiment holds constant
72
Use the three causal criteria to analyze an experiment’s ability to support a causal claim
covariance
temporal precedence
internal validity
73
Explain why control variables can help an experimenter eliminate design confounds
compare the IV to a group that wasn't exposed to stimuli and help determine if they are influencing the IV instead of the stimuli
74
Explain the difference between systematic and unsystematic variabilities
systematic
- another variable is changing with the IV
- problematic
unsystematic
- inconsistent/random change
- not a confound but make it hard to tell difference conditions
75
Describe random assignment and explain its role in establishing internal validity
help groups not become unfair/selection effects
76
Describe matching, explain its role in establishing internal validity, and explain situations in which matching may be preferred to random assignment
matching groups based on certain characteristics, helps avoid selection effects
77
Describe how the procedures for independent-groups and within-groups experiments are different
independent - each group is exposed to one IV level
within - each group is exposed to all levels of IV
78
Identify posttest-only and pretest/posttest designs, and explain when researchers might use each one
post - measured at the end of the study
pretest - measured at both the end and beginning of study, used to increase internal validity/temporal precedence
79
Explain the difference between concurrent-measures and repeated-measures designs
repeated - exposed to one condition at a time but back to back
concurrent - exposed to all conditions at the same time
80
Describe counterbalancing, and explain its role in the internal validity of a within-groups design
switch up order so no carryover/practice effect takes place, helps participants not learn about the study through practice
81
Interrogate the construct validity of a manipulated variable in an experiment, and explain the role of manipulation checks in establishing construct validity
add a question along with the IV of whether manipulation worked or not, but can reveal study if not done correctly
82
Explain why experimenters usually prioritize internal validity over external validity when it is difficult to achieve both
internal = easier to replicate
83
Identify effect size, d, and statistical significance, and explain what they mean for an experiment
mean the variables had an impact/interaction with each other
84
Describe the effect size using Cohen’s guidelines
small: more than .2
moderate: more than .5
large: more than .8
85
Explain the three threats to internal validity: design confounds, selection effects, and order effects
design: problem with design that is affecting the study
selection: one level of IV is different than the other
order: when being exposed to one condition affects how participants respond to other conditions
86
Identify and explain the following nine threats to internal validity: history, maturation, regression, attrition, testing, instrumentation, observer bias, demand characteristics, and placebo effects
history
- external factor that systematically effects participants
maturation
- change in behavior that emerges spontaneously over time
regression
- if the first measurement is an outlier, the second one will regress to the mean
attrition
- when certain groups are dropping out of study due to characteristics related to variables being studied
testing
- exposure to measure impacts response
instrumentation
- changes in the instrument/observers which may produce changes in outcomes
observer bias
- observers bias effecting results
demand
- participants guess what purpose of study is
placebo
87
Explain how comparison groups, double-blind studies, and other design choices can help researchers avoid many of these threats to ...
internal validity
88
Articulate the reasons why a study might result in null effects: not enough variance between groups, too much variance within groups, or a true null effect
not enough
- weak manipulation
- insensitive measures
- ceiling and floor effects
- design confound acting in reverse
too much
- measurement error
- individual differences
- situation noise
true
- there really is no difference!
89
Explain why large within-groups variance can obscure a between-groups difference
more overlap exists between the members of the groups
90
Describe three causes of within-group variance—measurement error, individual differences, and situation noise—and indicate how each might be reduced
measurement
- any factor that can inflate or deflate a person's true score on the DV
individual
- spread out scores within each group
situation
- external distraction that could cause variability within-groups that obscure between-groups differences
91
Articulate how a factorial design works
using factorial designs to study manipulated variables or participant variables
92
Explain reasons for conducting a factorial study.
see individual significance as well as interaction effects
93
Explain and identify interaction effects
interaction is almost always more important than the main effect
94
Identify two types of interaction effects
cross over
- it depends
- makes an X
spreading interaction
- only when
- start together than drift apart on graph
95
Estimate marginal means in a factorial design to look at main effects
calculate means for all variables to see main effects
96
Given a factorial notation (e.g., 2 × 2), identify the number of independent variables, the number of levels of each variable, the number of cells in the design, and the number of main effects and interactions that will be relevant
2 IVs with 2 levels each
4 cells
2 main effects
1 interaction
97
Explain the basic logic of three-way factorial designs
3 main effects
3 two-way interactions
1 three-way interaction
98
Interpret key words that indicate factorial-design language in a journal article
method section should show factorial notation (__x__x__)
results section will examine whether the main effects and interactions were significant
99
Interpret key words in popular media articles that indicate a factorial design
"it depends" or "only when"
look for participant variables
100
Define the following quasi-experimental designs: nonequivalent control group design, interrupted time-series design, and nonequivalent groups interrupted time-series design
nonequivalent control group design
- no random assignment
- at least one treatment and control group
- measuring only once
interrupted time-series design
- no comparison group
- measuring before, during, after event
nonequivalent groups interrupted time-series design
- no random assignment
- with comparison group
101
Using both the ____ and the _____, analyze whether a quasi-experimental design allows you to rule out internal validity threats
design; results
102
Explain the strengths and limitations of using a quasi-experimental design
real-world opportunities
external validity
ethics
construct validity and statistical validity
103
Interrogate quasi-experimental designs by asking about what three validities
construct
external
statistical
104
Explain three differences between small-N and large-N experiments
large
- participants are grouped
- basic and applied research
- group averages
small
- participants treated separately
- therapeutic settings
- data for each individual presented
105
Describe three small-N designs (stable-baseline designs, multiple-baseline designs, and reversal designs) and explain how each design addresses internal validity
stable
- observe behavior for baseline
multiple
- staggering intro of intervention across different individuals
reversal
- stop treatment to see if behavior reverts back
106
Give examples of questions you would ask about a small-N design to interrogate all four big validities
internal
- was study carefully designed?
external
- what are the goals of the study?
construct
- are the definitions and observations precise
statistical
- are they always relevant? (no)
107
Describe the differences among direct replication studies, conceptual replication studies, and
replication-plus-extension studies
direct
- repeating original study as closely as possible
conceptual
- not directly repeating, exploring same topic with different method/procedure
replication-plus-extension
- repeating original study as closely as possible while adding new variables to test new Q's
108
Give examples of types of replication projects in psychology: Open Science Collaboration (OSC) and Many Labs Projects (MLP)
OSC
- replicating studies only once
- lower success rate
MLP
- replicating each study more than once
- higher success rate
109
Explain why studies might fail to replicate
selective publication
problems with original study
- sample size (small)
- HARKing (hypothesis after the results are known)
- P-hacking (data fishing:running data until receive significant results)
contextually sensitive effects
number of replication attempts
110
Explain ways to improve scientific practices
larger sample sizes
report all analyses variable
open science collaboration/framework
preregistration
111
Explain what a meta-analysis does as well as its limitations
comprehensive review of literature
limitation: file drawer problem
- null results and opposite results rarely published
- need to be published to give accurate average
112
Describe the difference between generalization mode, in which ... , and theory-testing mode, in which ...
external validity is essential; external validity is less important than internal validity and may not be important at all
113
Articulate the mission of cultural psychology
to encourage researchers to test their theories in other cultural contexts; that is, to generalize to other cultures
114
Explain the issues with WEIRD participants
western, educated, industrialized, rich, democrat
115
Explain what ecological validity, field setting, and experimental realism are, and how they are related to external validity
ecological
- aspect of external validity, focus on whether lab study generalizes to real-world settings
experimental realism
- lab research can be just as realistic as research conducted in real world
116
Explain how to use effective search terms and techniques to find sources
and - search for all terms
or - search for one term or another
not - exclude the term
"" - search for entire phrase together
* truncation - search for anything that comes after the word (ex. stereotyp*)
117
CRAAP test for evaluating resources
currency - date of publish
relevance
authority - peer review
accuracy
purpose
118
Generate a reference list following the APA guidelines
4 things to look for
- hanging indent
- only beginning of sentence and after : should be capitalized
- journal/source should be italicized
- volume + numbers shouldn't be italicized
119
which ones are correct?
(Jones and Smith, 2012) or (Jones & Smith, 2012)
(Jones et al., 2019) or (Jones et al. 2019)
(Jones & Smith, 2012); (Jones et al., 2019)
