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CRJU 320 > Conceptualization > Flashcards

Conceptualization Flashcards

study for exam 2

1
Q

A statistical relationship between two variables; when one variable changes, the other tends to change as well.

Ice cream sales and drowning incidents

A

Correlation

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2
Q

A relationship where one variable directly affects or influences the other.

Smoking causes lung cancer.

A

Causation

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3
Q

The consistency of a measure; whether the results can be reproduced under the same conditions.

A

Reliability

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4
Q

Types of Reliability

three types

A

Stability, Representative, Inter-rater

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5
Q

Consistency across time.

type of reliability

A

Stability Reliability

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6
Q

Consistency across different groups.

type of reliability

A

Representative Reliability

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7
Q

Consistency across different raters or experts.

type of reliability

A

Inter-rater Reliability

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8
Q

The accuracy of a measure; whether the results represent what they are supposed to measure.

A

Validity

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9
Q

Types of Validity

Five types

A

Measurement, Face, Content, External, Internal

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10
Q

Whether the data or results reflect the intended variable.

Type of Validity

A

Measurement Validity

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11
Q

Whether the test items appear to measure what they are intended to measure.

Type of Validity

A

Face Validity

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12
Q

Whether the test covers all relevant parts of the subject.

Type of Validity

A

Content Validity

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13
Q

Whether the results can be generalized to other situations, groups, or events.

Type of Validity

A

External Validity

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14
Q

Whether the causal relationship is not influenced by other variables.

Type of Validity

A

Internal Validity

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15
Q

Threats to Validity

two types

A

external and internal

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16
Q

Types of External Threats

three threats

A

reactive testing, subject and variable interaction, multiple treatments

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17
Q

Participants’ knowledge of the study’s purpose affects their behavior.

external threat

A

Reactive Testing

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18
Q

Results only apply to the sample group.

external threat

A

Subject and Variable Interaction

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19
Q

Responses are altered by prior interactions.

external threat

A

Multiple Treatments

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20
Q

Types of Internal Validity Threats

six types

A

History, maturation, testing, satistical regression, bias selection of subjects, experimental mortality

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21
Q

Events during the research affect outcomes.

internal threats

A

History

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22
Q

Changes in participants over time affect the study.

internal threats

A

Maturation

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23
Q

Changes in measurement tools or methods affect results.

internal threats

A

Testing

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24
Q

Extreme scores skew results.

internal threats

A

Statistical Regression

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25
Q

Non-random selection affects results.

internal threats

A

Bias Selection of Subjects

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26
Q

Participants dropping out create uneven groups.

internal threats

A

Experimental Mortality

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27
Q

Defining abstract concepts (e.g., happiness, social justice) within a study.

A

Conceptualization

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28
Q

Defining and quantifying concepts for observation and analysis.

A

Measurement

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29
Q

Translating abstract concepts into specific, measurable variables.

A

Operationalization

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30
Q

Operationalization subgroups

three types

A

concepts, variable, indicator

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31
Q

General ideas or phenomena (e.g., crime).

Operationalization subgroups

A

Concepts

32
Q

The specific aspects measured (e.g., murder).

Operationalization subgroups

A

Variable

33
Q

Observable and measurable elements (e.g., number of arrests).

Operationalization subgroups

A

Indicator

34
Q

Types of variables

four types

A

independent, dependent, control, extraneous (confounding)

35
Q

The variable that stands alone and isn’t affected by other variables.

types of variables

A

Independent variable

ex. Individual sem. assignments

36
Q

The outcome or result influenced by the independent variable.

types of variables

A

Dependent Variable

ex. Overall semester grade

37
Q

Elements kept constant during a study.

types of variables

A

Control Variable

ex. race/gender

38
Q

Unaccounted-for variables that may affect the results.

types of variables

A

Extraneous (Confounding) Variables

ex. # hours of sleep

39
Q

Levels of Measurement

four levels

A

nominal, ordinal, interval, ratio

40
Q

Categories without order (e.g., gender, marital status).

A

Nominal

41
Q

Categories with order, but unequal intervals (e.g., satisfaction level).

A

Ordinal

42
Q

Ordered categories with equal intervals, no true zero (e.g., temperature).

A

Interval

43
Q

Ordered categories with equal intervals and a true zero (e.g., weight, height).

A

Ratio

44
Q

The entire group being studied.

A

population

45
Q

A subset of the population.

A

sample

46
Q

The process of selecting samples from the population.

A

Sampling

47
Q

A list of the population from which the sample is drawn.

A

Sampling Frame

48
Q

Types of Sampling

two types

A

probability and non-probability

49
Q

Every element has an equal chance of selection.

type of sampling

A

Probability Sampling

50
Q

types of probability sampling

four types

A

random, stratified, systematic, cluster

51
Q

Equal chance for all participants.

probability sampling

A

Random Sampling

52
Q

Population is divided into subgroups, and random samples are drawn from each.

probability sampling

A

Stratified Sampling

53
Q

Selection based on a predetermined rule (e.g., every nth participant).

probability sampling

A

Systematic Sampling

54
Q

Population divided into clusters, and random clusters are chosen.

probability sampling

A

Cluster Sampling

55
Q

Not every element has an equal chance of selection.

type of sampling

A

Non-probability Sampling

56
Q

types of non-probability sampling

four types

A

judgement, convinience, quota, snowball

57
Q

Selection based on the researcher’s judgment.

Non-probability Sampling

A

Judgment Sampling

58
Q

Selection based on availability.

Non-probability Sampling

A

Convenience Sampling

59
Q

Specific quotas are filled for subgroups.

Non-probability Sampling

A

Quota Sampling

60
Q

Participants refer others to the study.

Non-probability Sampling

A

Snowball Sampling

61
Q

The error that occurs when observing a sample rather than the whole population. It reflects the difference between the sample’s responses and the actual population.

A

Sampling Error

62
Q

How to minimize sampling error?

A

increase sample size

63
Q

Types of Measurements

three types

A

index, scale, composite

64
Q

Multiple variables combined into a single score.

Types of Measurements

A

index

65
Q

Weighting certain variables based on importance.

Types of Measurements

A

Scale

66
Q

Combination of variables into one score.

Types of Measurements

A

Composite

67
Q

Difference Between Correlation and Causation?

A

Correlation shows a relationship between two variables, but it doesn’t prove one causes the other. Example: Ice cream sales and drowning incidents rise together in summer but don’t cause each other.

68
Q

Importance of Distinguishing Correlation and Causation?

A

Misinterpreting correlation as causation can lead to false conclusions. Correct interpretation is crucial for drawing valid inferences.

69
Q

Difference Between Reliability and Validity?

A

Reliability refers to consistency, while validity refers to accuracy. A test can be reliable but not valid.

70
Q

Conceptualization vs. Operationalization?

A

Conceptualization involves defining abstract concepts; operationalization translates them into measurable variables. Operationalization ensures research can be analyzed.

71
Q

Importance of ensuring Accurate Indicators?

A

Indicators should align with the concept being measured and be clear and observable. Example: Using the number of drinks to measure binge drinking.

72
Q

Probability vs. Non-probability Sampling?

A

Probability sampling ensures every element has an equal chance of selection, improving generalizability. Non-probability sampling is used when random selection isn’t feasible.

73
Q

What is Stratified Sampling?

A

Dividing the population into strata (specific groups ex. m/f) and taking random samples from each group. It ensures all groups are represented and improves the sample’s representativeness.

74
Q

What is Snowball Sampling?

A

Participants refer others, used when the population is hard to access (e.g., hidden groups). Bias can occur as the sample may not represent the broader population.

75
Q

External vs. Internal Validity?

A

External validity refers to generalizability, while internal validity refers to ensuring the study’s findings aren’t affected by extraneous factors.

76
Q

What are Extraneous Variables?

A

These are unmeasured variables that can skew results, leading to incorrect conclusions about causality (e.g., studying a new teaching method without accounting for students’ prior knowledge).

CRJU 320 (1 decks)

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