Final Flashcards
(148 cards)
1
Q
The entire group of people about which we
wish to generalize
A
Population
2
Q
A portion of a population
A
Sample
3
Q
Sampling only those who are easy to contact
A
Convenience sampling
4
Q
Sampling only those who volunteer
A
Self-selection
5
Q
What are the 4 non-probability sampling techniques?
A
Convenience sampling
Quota sampling
Purposive sampling
Snowball sampling
6
Q
What are the 4 probability sampling techniques?
A
Simple random sampling
Systematic sampling
Stratified random sampling
Cluster sampling
7
Q
Every individual in the population
has an equal chance of being selected
A
Simple random sample
8
Q
Sample is selected according to a random starting point and a fixed periodic interval
A
Systematic sampling
9
Q
Strata are formed based on members’
shared attributes or characteristics
A
Stratified random sampling
10
Q
Uses “natural” but relatively heterogeneous
groupings in a population.
A
Cluster sampling
11
Q
An extension of convenience sampling, based on the characteristics of the sample and the purpose of the research
A
Purposive sampling
12
Q
Participants are chosen out of specific subgroups that are identified, with convenience sampling used to select the required number of participants from each subgroup
A
Quota sampling
13
Q
Participants recruit other participants, used to collect data when the desired sample characteristic is rare, or it is difficult to locate respondents
A
Snowball sampling
14
Q
Describes the data (variables) quantitatively
A
Descriptive statistics
15
Q
What are the differences between parameters and statistics?
A
Statistics describe samples, parameters describe populations
16
Q
A spreadsheet of our variables and their values
A
Data matrix
17
Q
A table which provides the number of or
frequency of each possible value
A
Frequency distribution
18
Q
A way of providing a graphical representation of the frequency of one variable of interest
A
Histogram or dot plot
19
Q
Measure of central tendency that can tell us where most of our scores in our dataset center around
A
Mean
20
Q
The middle score that splits the dataset in half
A
Median
21
Q
The most common number in a dataset
A
Mode
22
Q
What are the two ways to measure spread/variability in data?
A
Variance and standard deviation
23
Q
The average spread that each number in our dataset has around the mean
A
Variance
24
Q
The square root of the variance which provides a benchmark or indicator of spread for our dataset
A
Standard deviation
25
Specify how far away (in standard deviation units) one score is from the mean
Z-score
26
How does one calculate a z-score?
Difference between the individual score and the mean divided by the standard deviation
27
A degree of how one variable changes in
relation to the other variable
Covariance
28
A standardized covariance ranging from -1.0 to +1.0
Pearson's r
29
Tell us the strength of a relationship between two variables
Effect sizes
30
Tells us the distance between the means of two groups in standard deviation units
Cohen's d
31
A set of procedures that use the rules of probability to make inferences or generalizations about a population using sample data
Inferential statistics
32
What are three types of point estimates?
Percentage
Effect size
Strength of relationship
33
Range around the point estimate that often contains the true value (population value)
Confidence interval
34
What does the CI for a percentage estimate include?
Percent estimate +/- margin of error
35
On which three factors does the margin of error vary?
SD
Sample size
Level of confidence
36
What is the difference between CI and NHST?
CI represents a “new statistics” based on estimation
Null hypothesis significance testing is binary (yes/no)
37
What do H0 and H1 imply?
H0: Null hypothesis, no effect
H1: Alternate hypothesis, significant treatment effect
38
Describe the difference between a type l and type ll error
Type l: False positive, reject null hypothesis when it is true
Type ll: False negative, fail to reject null hypothesis when it is false
39
What hypothesis tests are appropriate for determining the mean difference for two groups?
Independent samples t-test, dependent samples t-test
40
What characteristics define independent samples t-tests?
Independent groups, between-subjects design
41
What characteristics define dependent-sample t-tests?
Dependent groups, within-subjects design
42
What hypothesis tests are appropriate for determining mean differences for two or more groups?
One-way ANOVA, repeated-measures ANOVA, two-way ANOVA
43
What is the f-ratio?
Between groups variability over within groups variability
44
What hypothesis test is appropriate for assessing the relationship between two numerical variables?
Pearson correlation: Correlation coefficient r and measure of effect r squared
45
Printed instruments that the respondents complete
Paper and pencil questionnaires
46
Online surveys created as Web forms with a database to store the answers
Electronic (e-surveys)
47
Respondents complete questionnaires that are completed on paper and returned via mail
Mail surveys
48
Collecting data using a telephone to contact respondents
Telephone surveys
49
Collecting data using a variation
of the different survey methods
Mixed-mode surveys
50
Collecting data face to face
Interviews
51
Questions that allow people to provide detailed answers.
Open-ended questions
52
Questions provide a limited selection of available responses.
Forced-choice questions
53
Questions use a rating scale to indicate level of agreement
Likert scale
54
Questions provide a numeric scale anchored by adjectives
Semantic differential
55
Which types of questions are appropriate for nominal measurements?
Dichotomous, demographic, forced choice
56
What types of questions are appropriate for ordinal measurements?
Rank order, scales, and likert-type
57
What types of questions are appropriate for interval measurements?
Semantic differential
58
Questions that require answers for two different options, leading to confusion
Double-barreled
59
Questions worded in such way that they imply a derogatory association
Negatively-worded questions
60
Responding in one set type of pattern
Response sets
61
Responding "yes" to all questions
Acquiescence
62
Choosing the moderate option
Fence sitting
63
Responding in a way that makes you look good
Socially desirable responding/faking good
64
The extent to which a measure is repeatable or stable; it refers to the consistency of a measure
Reliability
65
The extent to which the survey measures the construct we want to measure and no other related constructs
Validity
66
Refers to the degree to which
test results are consistent over time
Test-retest relibility
67
Respondents’ answers are compared on slightly different versions of a survey designed to measure the same construct
Parallel forms
68
Refers to the degree that the survey items are measuring the same construct
Internal consistency
69
What is the most common measure of internal consistency?
Cronbach's alpha
70
A measure of consistency wherein a survey is split into two equal parts and the results for each half are compared with one another
Split-half reliability
71
The extent to which a survey is subjectively viewed as measuring the concept
Face validity
72
Refers to the extent to which a measure represents all features of a given construct and focuses on the content of the survey items
Content validity
73
What are the two types of content validity?
Convergent and discriminant
74
The extent to which a measure is related to an outcome. It involves comparing our survey results with other measures or outcomes already considered valid.
Criterion-related validity
75
The extent to which a survey actually measures the construct it intended to measure and focuses on whether our survey measures a construct that cannot be directly observed.
Construct validity
76
What are the four types of observational research?
Naturalistic observation
Participant observation
Structured observation
Field experiment
77
Form of observation in which the observer is passive and does not intervene.
Naturalistic observation
78
Form of observation through which the observer can access normally "closed" situations (disguised on undisguised)
Participant observation
79
Form of observation used to observe behaviours that are difficult to see naturally
Structured observation
80
Manipulation of variables as in a true experiment that occurs in natural settings
Field experiment
81
When observers see what they expect to see
Observer bias
82
When participants confirm observer
expectations
Observer effects
83
What is one key way to minimize observer bias and effects?
Using a masked design
84
What are the three solutions to reactivity during observations?
Blend in, wait it out, or measure the behaviour's results
85
When participants react to being watched
Reactivity
86
When is it ethical to observe the behaviours of others without their consent?
When the behaviours take place in an environment that does not have an expectation of privacy
87
Associations that involve exactly two variables
Bivariate correlations
88
What makes a study correlational?
Having two measured variables and no manipulated variables
89
When interrogating association claims, what does construct validity refer to?
How well each variable was measured
90
When interrogating association claims, what does statistical validity refer to?
How well the data supports the conclusion
91
When interrogating association claims, what does external validity refer to?
Who the association can be generalized to
92
When interrogating association claims, what does internal validity refer to?
Whether or not a causal inference can be made from the association
93
How do outliers affect associations?
Skew the data to appear less associated than is likely true
94
How does restricting the range affect associations?
The degree of the association might appear minimized
95
What are the three causal criteria?
Covariance, temporal precedence, internal validity
96
Designs that involve more than two measured variables
Multivariate designs
97
Which causal criteria do longitudinal designs help address?
Temporal precedence
98
Which causal criteria do multiple regression analyses help address?
Internal validity
99
Another variable is generating the association between two other variables
Mediator
100
Another variable that controls the degree of association between two variables
Moderator
101
Influences that interfere with an accurate measurement between the independent and dependent variable
Confounds
102
What are two advantages of within-groups designs?
Participants are equivalent, require fewer participants
103
What is one strategy to avoid order effects?
Counterbalancing
104
When being exposed to one condition affects how participants respond to other conditions
Order effects
105
What are three disadvantages of within-groups designs?
Potential for order effects
Might not be practical or possible
Demand characteristics
106
Experiencing all levels of the independent variable (IV) changes the way participants act
Demand characteristics
107
The effect of one independent variable depends on the level of the other independent variable
Interaction
108
Design with two or more independent variables
Factorial
109
Differences between the levels of one independent variable across levels of the other independent variable
Main effect
110
What is more important: Interactions or main effects?
Interactions
111
When interrogating causal claims, what does construct validity refer to?
How well the variables were measured and manipulated
112
When interrogating causal claims, what does external validity refer to?
Who or what the causal claim can generalize to
113
When interrogating causal claims, what does statistical validity refer to?
How much, how precise, what else is known
114
When interrogating causal claims, what does internal validity refer to?
If there are any alternative explanations for the results
115
What are the six potential threats to internal validity in one-group or pretest-posttest designs?
Maturation threats
History threats
Regression threats
Attrition threats
Testing threats
Instrumentation threats
116
What are the three potential threats to internal validity in any study?
Observer bias
Demand characteristics
Placebo effects
117
Which three things could be responsible for a null effect?
Really no difference
Not enough between-group difference
Within-group variability obscured the group differences
118
When are quasi-experiments appropriate?
When researchers do not have full experimental control
119
What are the four types of quasi-experiments?
Nonequivalent control group posttest only
Nonequivalent control group pretest/posttest
Interrupted time-series
Nonequivalent control group interrupted time-series
120
Quasi-independent variable with dependent variable measured only once after exposure to the IV
Nonequivalent control group posttest-only
121
Quasi-independent variable with dependent variable measured once before and once after exposure to the IV
Nonequivalent control group pretest/posttest
122
A variable is measured before and after an “interruption”
Interrupted time-series
123
Two quasi-independent variables (group/condition, time) and a dependent variable
Nonequivalent control group interrupted time-series
124
What are three similarities between correlational studies and quasi-experiments?
Both may use independent-groups designs.
Neither use random assignment.
Neither use manipulated variables.
125
Designs in which only a few individuals are studied
Small-N designs
126
Small-N design in which baseline is assessed followed by introducing the intervention
Stable-baseline designs
127
Small-N design in which different baselines are assessed in relation to the effect of the intervention
Multiple-baseline designs
128
Small-N design in which the treatment is introduced and then taken away
Reversal designs
129
What are the major themes of qualitative research?
Answers in-depth social questions about “how” and “why”
Holistic, formative, thematic
Emphasis on studying things in their natural environment
Uses smaller sample sizes and more flexibility in sampling
130
What are the three major qualitative theories?
Grounded theory
Ethnography
Phenomenology
131
Qualitative comparative method that constructs theory from the process itself (inductive)
Grounded theory
132
Qualitative method that systematically studies patterns between people and cultures
Ethnography
133
Qualitative method that rejects data and themes altogether and collects thoughts and objects which influence each other
Phenomenology
134
What are three common methods of data collection for qualitative research?
Interviews
Focus groups
Participant observation
135
List of thematic codes with their definitions and several examples of what could be included and not included under this heading
Codebook
136
What are the three types of replication?
Direct replication
Conceptual replication
Replication-plus-extension
137
Exact replication of a study
Direct replication
138
Replication that maintains the same concept but changes the way it's operationalized/measured
Conceptual replication
139
Replication in which the original experimental design is maintained with an added component
Replication-plus-extension
140
Quantitative technique that calculates effect size across studies
Meta-analysis
141
What are four questionable research practices?
Underreporting null findings
HARKing
p-hacking
Using small samples
142
What does HARKing refer to?
Hypothesizing after the results are known
143
What are three examples of transparent research practices?
Open science
Preregistration
Encouraging large samples
144
An experimental group improves over time only because of natural development or spontaneous improvement
Maturation threat
145
An experimental group changes over time because of an external factor that affects all or most members of the group.
History threat
146
An experimental group whose average is extremely low (or high) at pretest will get better (or worse) over time because the random events that caused the extreme pretest scores do not recur the same way at posttest
Regression to the mean
147
An experimental group changes over time, but only because the most extreme cases have systematically dropped out and their scores are not included in the posttest
Attrition threat
148
A type of order effect: An experimental group changes over time because repeated testing has affected the participants. Practice effects (fatigue effects) are one subtype.
Testing threat
