Lecture 2 Flashcards

1
Q

Conceptualization

A

Identify the concepts you want to study. (e.g., empathy, prosocial behavior, violence)

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2
Q

Operationalization

A

Specify how you define or measure the concepts in your research question. (e.g., How do you measure empathy?)

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3
Q

Dependent variable

A

A variable that is hypothesized to vary depending on the influence of another variable (i.e., what you measure/observe)

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4
Q

Independent variable

A

A variable that is hypothesized to cause or lead to changes in another variable (i.e., what you define, control or manipulate, so that you can measure the effect on the dependent variable).

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5
Q

non-manipulable

A

Note that many variables in social research are (e.g., gender, ethnicity, socioeconomic status).

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6
Q

Nominal level

A

no mathematical interpretation; categories vary in quality. e.g. omnivore, vegetarian, vegan, or fruitarian

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7
Q

Ordinal level

A

categories have a logical order. e.g. fail, pass, or distinction

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8
Q

discrete measures

A

Measures at the nominal and ordinal level are also called

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9
Q

Interval level

A

equal intervals represent equal differences. e.g. temperature, year

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10
Q

Ratio level

A

contains absolute zero e.g. reaction time, distance

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11
Q

continuous measures

A

Measures at the interval and ratio level are also called

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12
Q

validity

A

indicates whether conclusions are well-founded.

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13
Q

Internal validity

A

Are the causal relations between variables real?

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14
Q

Causality

A

A concern with establishing a “cause and effect” connection between variables, rather than the mere relationship between them

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15
Q

Confounding variables

A

variables beyond the operationalized dependent or independent variables that could influence the findings.

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16
Q

Experimenter bias

A

the behavior or actions of the experimenter may influence the responses of the participants or the data collection in general

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17
Q

Single blind experiment

A

Information that could bias the results is withheld from the participants.

18
Q

Double-blind experiment

A

Information that could bias the results is withheld from both the participants and the experimenter.

19
Q

External validity

A

Can results be generalized to other settings or other populations

20
Q

Reactivity

A

Participants adjust their behavior/responses because they know that they are being observed

21
Q

Demand characteristics

A

Participants adjust their behavior/responses according to what they believe the researcher expects or hypothesizes.

22
Q

Ecological validity

A

Are findings applicable to everyday life? Does the research setting resemble a “real-world” situation

23
Q

Reliability

A

Are measures consistent? (i.e., do they give the same results over time when the phenomeon has not changed?)

24
Q

Measurement validity

A

Type of validity associated with whether an indicator really measures a concept

25
Q

Face validity

A

does the measure reflect the concept in question “at face value

26
Q

Content validity

A

Does the measure cover the full range of the concept’s meaning? (e.g., does the measure cover different aspects of scientific curiosity?).

27
Q

Criterion validity

A

Compare scores on the newly developed measure with scores on another more direct or already validated outcome measure of the same phenomenon

28
Q

Concurrent validity

A

Compare the scores on the measure with another outcome measured at the same time (e.g., is the measure positively related to the extent to which people choose to read short stories about scientific discoveries?

29
Q

Predictive validity

A

Can the measure predict a future outcome? (e.g., can the measure predict who often reads popular science books/magazines or visits popular science websites?)

30
Q

Construct validity

A

showing that a measure corresponds with established measures of theoretically related concepts. (e.g., is the scientific curiosity scale positively related to a validated general curiosity questionnaire?)

31
Q

Discriminant validity

A

showing that a measure is not related (or negatively related) to measures of concepts that should theoretically not be related

32
Q

Triangulation

A

the use of two or more methods to study the same research question, or the use of two ore more measures to indicate the same variable.

33
Q

Convergence

A

between measures increases confidence in the validity of the measures

34
Q

Divergence

A

between measures could indicate measurement error or that the measures genuinely tap different concepts

35
Q

Cross-sectional design

A
  • A study, measuring more than one case at a single point in time to test variation (often a survey/ questionnaire)
  • Quantitative data
  • Examine relationships between variables (i.e., correlation)
  • no conclusions about causality (= weak internal validity)!
36
Q

Longitudinal design

A
  • Research in which data is collected at two or more points in time
  • Very intensive and expensive in terms of time and resources
  • Potential issues with attrition and subject fatigue
37
Q

Panel study

A

cross-sectional sample that is followed over time

38
Q

Cohort study

A

sample consists of a group that experiences some event (such as being born) in a selected time period

39
Q

Case study design

A
  • Detailed and extensive analysis of one case.

- Often qualitative, but can also be quantitative

40
Q

Comparative design

A
  • Comparing two or more cases, or two or more samples.

- Often quantitative in survey form, but can also be qualitative