Conceptualization

Question 1

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

Ice cream sales and drowning incidents

Answer 1

Correlation

Question 2

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

Smoking causes lung cancer.

Answer 2

Causation

Question 3

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

Answer 3

Reliability

Question 4

Types of Reliability

three types

Answer 4

Stability, Representative, Inter-rater

Question 5

Consistency across time.

type of reliability

Answer 5

Stability Reliability

Question 6

Consistency across different groups.

type of reliability

Answer 6

Representative Reliability

Question 7

Consistency across different raters or experts.

type of reliability

Answer 7

Inter-rater Reliability

Question 8

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

Answer 8

Validity

Question 9

Types of Validity

Five types

Answer 9

Measurement, Face, Content, External, Internal

Question 10

Whether the data or results reflect the intended variable.

Type of Validity

Answer 10

Measurement Validity

Question 11

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

Type of Validity

Answer 11

Face Validity

Question 12

Whether the test covers all relevant parts of the subject.

Type of Validity

Answer 12

Content Validity

Question 13

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

Type of Validity

Answer 13

External Validity

Question 14

Whether the causal relationship is not influenced by other variables.

Type of Validity

Answer 14

Internal Validity

Question 15

Threats to Validity

two types

Answer 15

external and internal

Question 16

Types of External Threats

three threats

Answer 16

reactive testing, subject and variable interaction, multiple treatments

Question 17

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

external threat

Answer 17

Reactive Testing

Question 18

Results only apply to the sample group.

external threat

Answer 18

Subject and Variable Interaction

Question 19

Responses are altered by prior interactions.

external threat

Answer 19

Multiple Treatments

Question 20

Types of Internal Validity Threats

six types

Answer 20

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

Question 21

Events during the research affect outcomes.

internal threats

Answer 21

History

Question 22

Changes in participants over time affect the study.

internal threats

Answer 22

Maturation

Question 23

Changes in measurement tools or methods affect results.

internal threats

Answer 23

Testing

Question 24

Extreme scores skew results.

internal threats

Answer 24

Statistical Regression

Question 25

Non-random selection affects results. | internal threats

Answer 25

Bias Selection of Subjects

Question 26

Participants dropping out create uneven groups. | internal threats

Answer 26

Experimental Mortality

Question 27

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

Answer 27

Conceptualization

Question 28

Defining and quantifying concepts for observation and analysis.

Answer 28

Measurement

Question 29

Translating abstract concepts into specific, measurable variables.

Answer 29

Operationalization

Question 30

Operationalization subgroups | three types

Answer 30

concepts, variable, indicator

Question 31

General ideas or phenomena (e.g., crime). | Operationalization subgroups

Answer 31

Concepts

Question 32

The specific aspects measured (e.g., murder). | Operationalization subgroups

Answer 32

Variable

Question 33

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

Answer 33

Indicator

Question 34

Types of variables | four types

Answer 34

independent, dependent, control, extraneous (confounding)

Question 35

The variable that stands alone and isn't affected by other variables. | types of variables

Answer 35

Independent variable | ex. Individual sem. assignments

Question 36

The outcome or result influenced by the independent variable. | types of variables

Answer 36

Dependent Variable | ex. Overall semester grade

Question 37

Elements kept constant during a study. | types of variables

Answer 37

Control Variable | ex. race/gender

Question 38

Unaccounted-for variables that may affect the results. | types of variables

Answer 38

Extraneous (Confounding) Variables | ex. # hours of sleep

Question 39

Levels of Measurement | four levels

Answer 39

nominal, ordinal, interval, ratio

Question 40

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

Answer 40

Nominal

Question 41

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

Answer 41

Ordinal

Question 42

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

Answer 42

Interval

Question 43

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

Answer 43

Ratio

Question 44

The entire group being studied.

Answer 44

population

Question 45

A subset of the population.

Answer 45

sample

Question 46

The process of selecting samples from the population.

Answer 46

Sampling

Question 47

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

Answer 47

Sampling Frame

Question 48

Types of Sampling | two types

Answer 48

probability and non-probability

Question 49

Every element has an equal chance of selection. | type of sampling

Answer 49

Probability Sampling

Question 50

types of probability sampling | four types

Answer 50

random, stratified, systematic, cluster

Question 51

Equal chance for all participants. | probability sampling

Answer 51

Random Sampling

Question 52

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

Answer 52

Stratified Sampling

Question 53

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

Answer 53

Systematic Sampling

Question 54

Population divided into clusters, and random clusters are chosen. | probability sampling

Answer 54

Cluster Sampling

Question 55

Not every element has an equal chance of selection. | type of sampling

Answer 55

Non-probability Sampling

Question 56

types of non-probability sampling | four types

Answer 56

judgement, convinience, quota, snowball

Question 57

Selection based on the researcher's judgment. | Non-probability Sampling

Answer 57

Judgment Sampling

Question 58

Selection based on availability. | Non-probability Sampling

Answer 58

Convenience Sampling

Question 59

Specific quotas are filled for subgroups. | Non-probability Sampling

Answer 59

Quota Sampling

Question 60

Participants refer others to the study. | Non-probability Sampling

Answer 60

Snowball Sampling

Question 61

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.

Answer 61

Sampling Error

Question 62

How to minimize sampling error?

Answer 62

increase sample size

Question 63

Types of Measurements | three types

Answer 63

index, scale, composite

Question 64

Multiple variables combined into a single score. | Types of Measurements

Answer 64

index

Question 65

Weighting certain variables based on importance. | Types of Measurements

Answer 65

Scale

Question 66

Combination of variables into one score. | Types of Measurements

Answer 66

Composite

Question 67

Difference Between Correlation and Causation?

Answer 67

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.

Question 68

Importance of Distinguishing Correlation and Causation?

Answer 68

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

Question 69

Difference Between Reliability and Validity?

Answer 69

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

Question 70

Conceptualization vs. Operationalization?

Answer 70

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

Question 71

Importance of ensuring Accurate Indicators?

Answer 71

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

Question 72

Probability vs. Non-probability Sampling?

Answer 72

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

Question 73

What is Stratified Sampling?

Answer 73

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.

Question 74

What is Snowball Sampling?

Answer 74

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.

Question 75

External vs. Internal Validity?

Answer 75

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

Question 76

What are Extraneous Variables?

Answer 76

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).