Exam 2 Flashcards

(59 cards)

1
Q

Open-sourced questions

A

Allows respondents to answer in any way they like

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2
Q

Forced choice questions

A

People giving their opinions by choosing the best of two or more options

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3
Q

Likert Scale

A

Presented with a statement and then asked how they would indicate their degree of agreement

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4
Q

Semantic differential format

A

Respondents asked to rate a target object using a numeric scale that is anchored with adjectives

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5
Q

Leading Questions

A

Framing a question as positive or negative will lead an answer that will give an answer that goes along with the wording of the question

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6
Q

Negatively worded question

A

Unnecessarily complicated questions that can cause cognitive difficulty for people

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7
Q

Response sets/nondifferentiation

A

Type of shortcut respondents can take when answering survey questions

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8
Q

Acquiescence/yea-saying

A

Respondents say yes to something without reading the question carefully (reason for including inverse worded questions)

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9
Q

Fence sitting

A

Playing it safe and answering all of the questions in the middle (this may be a reason to include even numbered questions.

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10
Q

Socially desirable responding/faking good

A

Because a respondent is shy, embarrassed or worried about answering wit an unpopular opinon, they will not tell the truth on a survey or another self-report measure. A similar problem would be faking bad

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11
Q

Observational Research

A

A researcher watches people or animals and systematically records what they are doing

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12
Q

Observer Bias

A

When the observers’ expectation influence their interpretation of the participants behavior in the outcome of the study

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13
Q

Masked Design/Blind design

A

When observers are unaware of the conditions to which participants have been assigned and unaware of what the study is about

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14
Q

Generalizability

A

Does the sample represent the population

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15
Q

Population

A

The entire set of people or products in which you are interested in

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16
Q

Sample

A

A smaller set of the population

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17
Q

Census

A

A survey of the entire population

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18
Q

Population of interest

A

The population that the researchers want to generalize

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19
Q

Biased sample/unrepresented sample

A

Members of the population of interest have a much higher probability of being included in the sample compared to other members

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20
Q

Representative sample/unbiased sample

A

All members of the population have an equal chance of being included in the sample

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21
Q

Convenience sampling

A

Using a sample of people who are readily available to participate

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22
Q

Self-selection

A

When a sample is known to contain only people who volunteer to participate

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23
Q

Simple Random Sampling

A

A hat with tickets in it

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24
Q

Cluster sampling

A

Clusters of participants within a population of interest are randomly selected, then all individuals in each selected cluster are used

25
Multistage sampling
Two random samples are selected: a random sample of clusters and then a random set of people within clusters
26
Stratified random sampling
The researcher selects particular demographic categories on purpose and then randomly selects individuals within each of the categories
27
Oversampling
The researcher intentionally over represents one or more groups
28
Systematic sampling
Using a computer or a random number table, the researcher selects a random number then counts off
29
Random assignment
Only in experimental designs, researchers place participants into different groups and are assigned at random
30
Purposive Sampling
When researchers only want to study certain kinds of people and only recruit those particular participants
31
Snowball sampling
Participants are asked to recommend people to the study
32
Quota sampling
The researcher identifies subsets of the population of interest and then sets a target number for each category in the sample
33
Bivariate correlation/bivariate associationn
An association that involves exactly two variables
34
Categorical variable
The value falls in either one category or another
35
Quantitative variable
The value of 7 means more than 6, 6 means more than 5 and so on
36
T test
When testing associations and only one variable is categorical
37
Effect size
Describes the strength of an association
38
Statistical significance
The conclusion a researcher reaches regarding how likely it is they'd get a correlation of that size just by chance, assuming there's no correlation in the real world
39
Outlier
An extreme score that stands out over the pack
40
Restriction of range
If there is not a full range of scores on one of the variables in the association, it can make the correlation appear smaller than it really is
41
Curvilinear association/curvilinear correlation
The relationship between two variables that is not a straight line
42
Causal temptation
The powerful automatic tendency to make a causal inference from any association claim we read
43
The three causal criteria
Covariance of the cause and effect, temporal precedence, Internal validity
44
Covariance of cause and effect
There must be a correlation, or association between the cause variable and the effect variable
45
Temporal precedence
The causal variable must precede the effect variable; it must come first in time
46
Internal validity
There must be no plausible alternative explanations for the relationship between the two variables
47
Directionality problem/temporal precedence
We don't know which variable came first
48
Third-variable problem
When we can come up with an alternative explanation for the association between two variables, that alternative explanation is the third variable
49
Moderator
When the relationship between two variables changes depending on the level of another variable, that other variable is the moderator
50
Covariance
The two variables are clearly related
51
Temporal precedence
Ability to show which variable comes first
52
Internal validity
Is it more likely to be explained by a third variable?
53
Longitudinal design
Measuring the same variables in the same people at several points in time
54
Cross-sectional correlations
Testing to see whether two variables, measured at the same point in time are correlated
55
Autocorrelations
They determine the correlation of one variable with itself, measured on two different occasions
56
Cross-lag correlations
Show whether the earlier measure of one variable is associated with the later measure of the other variable- researchers are most interested in this
57
Parsimony
The degree to which a good scientific theory provides the simplest explanation of some phenomenon
58
Mediator/mediating variable
The explanations for causal relationships- only established when the proposed causal variable is measured first in a study and then is followed by the mediating variable, and the followed by the proposed outcome variable
59
Survey/Poll
A method of answering questions to people, whether on the phone, in person, written questionnaires or online