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Research Methods and Ethics > Final > Flashcards

Final Flashcards

1
Q

The entire group of people about which we
wish to generalize

A

Population

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2
Q

A portion of a population

A

Sample

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3
Q

Sampling only those who are easy to contact

A

Convenience sampling

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4
Q

Sampling only those who volunteer

A

Self-selection

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5
Q

What are the 4 non-probability sampling techniques?

A

Convenience sampling
Quota sampling
Purposive sampling
Snowball sampling

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6
Q

What are the 4 probability sampling techniques?

A

Simple random sampling
Systematic sampling
Stratified random sampling
Cluster sampling

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7
Q

Every individual in the population
has an equal chance of being selected

A

Simple random sample

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8
Q

Sample is selected according to a random starting point and a fixed periodic interval

A

Systematic sampling

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9
Q

Strata are formed based on members’
shared attributes or characteristics

A

Stratified random sampling

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10
Q

Uses “natural” but relatively heterogeneous
groupings in a population.

A

Cluster sampling

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11
Q

An extension of convenience sampling, based on the characteristics of the sample and the purpose of the research

A

Purposive sampling

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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

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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

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14
Q

Describes the data (variables) quantitatively

A

Descriptive statistics

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15
Q

What are the differences between parameters and statistics?

A

Statistics describe samples, parameters describe populations

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16
Q

A spreadsheet of our variables and their values

A

Data matrix

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17
Q

A table which provides the number of or
frequency of each possible value

A

Frequency distribution

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18
Q

A way of providing a graphical representation of the frequency of one variable of interest

A

Histogram or dot plot

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19
Q

Measure of central tendency that can tell us where most of our scores in our dataset center around

A

Mean

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20
Q

The middle score that splits the dataset in half

A

Median

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21
Q

The most common number in a dataset

A

Mode

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22
Q

What are the two ways to measure spread/variability in data?

A

Variance and standard deviation

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23
Q

The average spread that each number in our dataset has around the mean

A

Variance

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24
Q

The square root of the variance which provides a benchmark or indicator of spread for our dataset

A

Standard deviation

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25
Q

Specify how far away (in standard deviation units) one score is from the mean

A

Z-score

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26
Q

How does one calculate a z-score?

A

Difference between the individual score and the mean divided by the standard deviation

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27
Q

A degree of how one variable changes in
relation to the other variable

A

Covariance

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28
Q

A standardized covariance ranging from -1.0 to +1.0

A

Pearson’s r

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29
Q

Tell us the strength of a relationship between two variables

A

Effect sizes

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30
Q

Tells us the distance between the means of two groups in standard deviation units

A

Cohen’s d

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31
Q

A set of procedures that use the rules of probability to make inferences or generalizations about a population using sample data

A

Inferential statistics

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32
Q

What are three types of point estimates?

A

Percentage
Effect size
Strength of relationship

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33
Q

Range around the point estimate that often contains the true value (population value)

A

Confidence interval

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34
Q

What does the CI for a percentage estimate include?

A

Percent estimate +/- margin of error

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35
Q

On which three factors does the margin of error vary?

A

SD
Sample size
Level of confidence

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36
Q

What is the difference between CI and NHST?

A

CI represents a “new statistics” based on estimation
Null hypothesis significance testing is binary (yes/no)

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37
Q

What do H0 and H1 imply?

A

H0: Null hypothesis, no effect
H1: Alternate hypothesis, significant treatment effect

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38
Q

Describe the difference between a type l and type ll error

A

Type l: False positive, reject null hypothesis when it is true
Type ll: False negative, fail to reject null hypothesis when it is false

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39
Q

What hypothesis tests are appropriate for determining the mean difference for two groups?

A

Independent samples t-test, dependent samples t-test

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40
Q

What characteristics define independent samples t-tests?

A

Independent groups, between-subjects design

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41
Q

What characteristics define dependent-sample t-tests?

A

Dependent groups, within-subjects design

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42
Q

What hypothesis tests are appropriate for determining mean differences for two or more groups?

A

One-way ANOVA, repeated-measures ANOVA, two-way ANOVA

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43
Q

What is the f-ratio?

A

Between groups variability over within groups variability

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44
Q

What hypothesis test is appropriate for assessing the relationship between two numerical variables?

A

Pearson correlation: Correlation coefficient r and measure of effect r squared

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45
Q

Printed instruments that the respondents complete

A

Paper and pencil questionnaires

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46
Q

Online surveys created as Web forms with a database to store the answers

A

Electronic (e-surveys)

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47
Q

Respondents complete questionnaires that are completed on paper and returned via mail

A

Mail surveys

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48
Q

Collecting data using a telephone to contact respondents

A

Telephone surveys

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49
Q

Collecting data using a variation
of the different survey methods

A

Mixed-mode surveys

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50
Q

Collecting data face to face

A

Interviews

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51
Q

Questions that allow people to provide detailed answers.

A

Open-ended questions

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52
Q

Questions provide a limited selection of available responses.

A

Forced-choice questions

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53
Q

Questions use a rating scale to indicate level of agreement

A

Likert scale

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54
Q

Questions provide a numeric scale anchored by adjectives

A

Semantic differential

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55
Q

Which types of questions are appropriate for nominal measurements?

A

Dichotomous, demographic, forced choice

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56
Q

What types of questions are appropriate for ordinal measurements?

A

Rank order, scales, and likert-type

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57
Q

What types of questions are appropriate for interval measurements?

A

Semantic differential

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58
Q

Questions that require answers for two different options, leading to confusion

A

Double-barreled

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59
Q

Questions worded in such way that they imply a derogatory association

A

Negatively-worded questions

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60
Q

Responding in one set type of pattern

A

Response sets

61
Q

Responding “yes” to all questions

A

Acquiescence

62
Q

Choosing the moderate option

A

Fence sitting

63
Q

Responding in a way that makes you look good

A

Socially desirable responding/faking good

64
Q

The extent to which a measure is repeatable or stable; it refers to the consistency of a measure

A

Reliability

65
Q

The extent to which the survey measures the construct we want to measure and no other related constructs

A

Validity

66
Q

Refers to the degree to which
test results are consistent over time

A

Test-retest relibility

67
Q

Respondents’ answers are compared on slightly different versions of a survey designed to measure the same construct

A

Parallel forms

68
Q

Refers to the degree that the survey items are measuring the same construct

A

Internal consistency

69
Q

What is the most common measure of internal consistency?

A

Cronbach’s alpha

70
Q

A measure of consistency wherein a survey is split into two equal parts and the results for each half are compared with one another

A

Split-half reliability

71
Q

The extent to which a survey is subjectively viewed as measuring the concept

A

Face validity

72
Q

Refers to the extent to which a measure represents all features of a given construct and focuses on the content of the survey items

A

Content validity

73
Q

What are the two types of content validity?

A

Convergent and discriminant

74
Q

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.

A

Criterion-related validity

75
Q

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.

A

Construct validity

76
Q

What are the four types of observational research?

A

Naturalistic observation
Participant observation
Structured observation
Field experiment

77
Q

Form of observation in which the observer is passive and does not intervene.

A

Naturalistic observation

78
Q

Form of observation through which the observer can access normally “closed” situations (disguised on undisguised)

A

Participant observation

79
Q

Form of observation used to observe behaviours that are difficult to see naturally

A

Structured observation

80
Q

Manipulation of variables as in a true experiment that occurs in natural settings

A

Field experiment

81
Q

When observers see what they expect to see

A

Observer bias

82
Q

When participants confirm observer
expectations

A

Observer effects

83
Q

What is one key way to minimize observer bias and effects?

A

Using a masked design

84
Q

What are the three solutions to reactivity during observations?

A

Blend in, wait it out, or measure the behaviour’s results

85
Q

When participants react to being watched

A

Reactivity

86
Q

When is it ethical to observe the behaviours of others without their consent?

A

When the behaviours take place in an environment that does not have an expectation of privacy

87
Q

Associations that involve exactly two variables

A

Bivariate correlations

88
Q

What makes a study correlational?

A

Having two measured variables and no manipulated variables

89
Q

When interrogating association claims, what does construct validity refer to?

A

How well each variable was measured

90
Q

When interrogating association claims, what does statistical validity refer to?

A

How well the data supports the conclusion

91
Q

When interrogating association claims, what does external validity refer to?

A

Who the association can be generalized to

92
Q

When interrogating association claims, what does internal validity refer to?

A

Whether or not a causal inference can be made from the association

93
Q

How do outliers affect associations?

A

Skew the data to appear less associated than is likely true

94
Q

How does restricting the range affect associations?

A

The degree of the association might appear minimized

95
Q

What are the three causal criteria?

A

Covariance, temporal precedence, internal validity

96
Q

Designs that involve more than two measured variables

A

Multivariate designs

97
Q

Which causal criteria do longitudinal designs help address?

A

Temporal precedence

98
Q

Which causal criteria do multiple regression analyses help address?

A

Internal validity

99
Q

Another variable is generating the association between two other variables

A

Mediator

100
Q

Another variable that controls the degree of association between two variables

A

Moderator

101
Q

Influences that interfere with an accurate measurement between the independent and dependent variable

A

Confounds

102
Q

What are two advantages of within-groups designs?

A

Participants are equivalent, require fewer participants

103
Q

What is one strategy to avoid order effects?

A

Counterbalancing

104
Q

When being exposed to one condition affects how participants respond to other conditions

A

Order effects

105
Q

What are three disadvantages of within-groups designs?

A

Potential for order effects
Might not be practical or possible
Demand characteristics

106
Q

Experiencing all levels of the independent variable (IV) changes the way participants act

A

Demand characteristics

107
Q

The effect of one independent variable depends on the level of the other independent variable

A

Interaction

108
Q

Design with two or more independent variables

A

Factorial

109
Q

Differences between the levels of one independent variable across levels of the other independent variable

A

Main effect

110
Q

What is more important: Interactions or main effects?

A

Interactions

111
Q

When interrogating causal claims, what does construct validity refer to?

A

How well the variables were measured and manipulated

112
Q

When interrogating causal claims, what does external validity refer to?

A

Who or what the causal claim can generalize to

113
Q

When interrogating causal claims, what does statistical validity refer to?

A

How much, how precise, what else is known

114
Q

When interrogating causal claims, what does internal validity refer to?

A

If there are any alternative explanations for the results

115
Q

What are the six potential threats to internal validity in one-group or pretest-posttest designs?

A

Maturation threats
History threats
Regression threats
Attrition threats
Testing threats
Instrumentation threats

116
Q

What are the three potential threats to internal validity in any study?

A

Observer bias
Demand characteristics
Placebo effects

117
Q

Which three things could be responsible for a null effect?

A

Really no difference
Not enough between-group difference
Within-group variability obscured the group differences

118
Q

When are quasi-experiments appropriate?

A

šWhen researchers do not have full experimental control

119
Q

What are the four types of quasi-experiments?

A

Nonequivalent control group posttest only
š
Nonequivalent control group pretest/posttest
š
Interrupted time-series
š
Nonequivalent control group interrupted time-series

120
Q

Quasi-independent variable with dependent variable measured only once after exposure to the IV

A

Nonequivalent control group posttest-only

121
Q

Quasi-independent variable with dependent variable measured once before and once after exposure to the IV

A

Nonequivalent control group pretest/posttest

122
Q

A variable is measured before and after an “interruption”

A

Interrupted time-series

123
Q

Two quasi-independent variables (šgroup/condition, time) and a dependent variable

A

Nonequivalent control group interrupted time-series

124
Q

What are three similarities between correlational studies and quasi-experiments?

A

Both may use independent-groups designs.
šNeither use random assignment.
šNeither use manipulated variables.

125
Q

Designs in which only a few individuals are studied

A

Small-N designs

126
Q

Small-N design in which baseline is assessed followed by introducing the intervention

A

Stable-baseline designs

127
Q

Small-N design in which different baselines are assessed in relation to the effect of the intervention

A

Multiple-baseline designs

128
Q

Small-N design in which the treatment is introduced and then taken away

A

Reversal designs

129
Q

What are the major themes of qualitative research?

A

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
Q

What are the three major qualitative theories?

A

Grounded theory
Ethnography
Phenomenology

131
Q

Qualitative comparative method that constructs theory from the process itself (inductive)

A

Grounded theory

132
Q

Qualitative method that systematically studies patterns between people and cultures

A

Ethnography

133
Q

Qualitative method that rejects data and themes altogether and collects thoughts and objects which influence each other

A

Phenomenology

134
Q

What are three common methods of data collection for qualitative research?

A

Interviews
Focus groups
Participant observation

135
Q

List of thematic codes with their definitions and several examples of what could be included and not included under this heading

A

Codebook

136
Q

What are the three types of replication?

A

Direct replication
Conceptual replication
Replication-plus-extension

137
Q

Exact replication of a study

A

Direct replication

138
Q

Replication that maintains the same concept but changes the way it’s operationalized/measured

A

Conceptual replication

139
Q

Replication in which the original experimental design is maintained with an added component

A

Replication-plus-extension

140
Q

Quantitative technique that calculates effect size across studies

A

Meta-analysis

141
Q

What are four questionable research practices?

A

Underreporting null findings
HARKing
p-hacking
Using small samples

142
Q

What does HARKing refer to?

A

Hypothesizing after the results are known

143
Q

What are three examples of transparent research practices?

A

Open science
Preregistration
Encouraging large samples

144
Q

An experimental group improves over time only because of natural development or spontaneous improvement

A

Maturation threat

145
Q

An experimental group changes over time because of an external factor that affects all or most members of the group.

A

History threat

146
Q

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

A

Regression to the mean

147
Q

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

A

Attrition threat

148
Q

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.

A

Testing threat

Research Methods and Ethics (2 decks)

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