Statistics

Question 1

95% confidence interval

Answer 1

A range around an estimate that, would include the true population value 95% of the time, with repeated sampling

Question 2

Attrition

Answer 2

Loss of participants during a study, especially in longitudinal research, which can threaten validity.

Question 3

Bias (in a statistical estimate)

Answer 3

Systematic error causing an estimate to differ from the true population value.

Question 4

Causal inference

Answer 4

Process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system.

Question 5

Coefficient of determination (R²)

Answer 5

Proportion of the variation in the dependent variable explained by the independent variables in regression

Question 6

Concept and measure

Answer 6

A concept is an abstract idea; a measure is the empirical indicator used to represent it (process of quantifying ).

Question 7

Conceptualization

Answer 7

Process of defining abstract concepts into clear, specific terms for a research study.

Question 8

Construct

Answer 8

A theoretical/abstract concept that cannot be directly observed but can be measured through mulitple indicators/variables.

Question 9

Control variable

Answer 9

A variable that is held constant during an analysis to prevent it from influencing the relationship between the independent and dependent variables

Question 10

Convenience sample

Answer 10

(Non-probability sampling method) Sample selected based on easy accessibility to the researcher, rather than probability, leading to limited generalizability.

Question 11

Convergent validity

Answer 11

A statistical measure used to evaluate whether different measures of the same construct are correlated.

Question 12

Correlation (Pearson’s)

Answer 12

Statistic that quantifies the strength and direction of a linear relationship between two continuous variables.

Question 13

Cronbach’s alpha

Answer 13

a measure/coefficient of the internal consistency among items forming a scale

Question 14

Descriptive and inferential statistics

Answer 14

Descriptive statistics summarize data; inferential statistics allow generalization from a sample to a population (uses a sample to make predictions or generalizations about a larger population)

Question 15

Discriminant validity

Answer 15

A statistical measure which tests the extent to which a measure is distinct from measures of different constructs.

Question 16

Double-barrelled question

Answer 16

Survey question that asks about two things at once, reducing clarity and reliability of the answer (forcing respondents to provide a single answer for multiple issues)

Question 17

Dummy or indicator variable

Answer 17

Binary variable (0 or 1) representing a category in regression analysis. It indicates the absence or presence of some categorical effect.

Question 18

Error term or disturbance

Answer 18

A component in a statistical model that accounts for the difference between the predicted values and the actual outcomes.
Represents variation in a dependent variable that the regression model’s independent variables cannot explain.

Question 19

Experiment and controlled experiment

Answer 19

An experiment is a procedure designed to test a hypothesis; controlled experiment is a specific type of experiment where all variables are kept constant except one (independent variable), to examine its effect on the outcome (dependent variable).

Question 20

External validity

Answer 20

Extent to which study findings can be generalized to other contexts.

Question 21

Independent and dependent variable

Answer 21

An independent variable is the factor that is changed or manipulated in an experiment to see its effect, while a dependent variable is the observed effect that is measured

Question 22

Index and scale

Answer 22

An index is a measure that sums or averages multiple items multiple equally; a scale weights items based on intensity of responses.

Question 23

Indicator

Answer 23

Observable measure used to represent an abstract construct or variable.

Question 24

Interaction term

Answer 24

Product of two variables in regression showing how their joint effect differs from their individual effects.

Question 25

Intercept and slope in simple regression

Answer 25

Intercept is the predicted value of Y (dependent variable) when X = 0 (independent variable = 0) ; slope is the expected change in Y per unit change in X.

Question 26

Internal validity

Answer 26

Extent to which a piece of evidence supports a claim about cause and effect (causal conclusion can be justified), within the context of a particular study

Question 27

Interval measurement

Answer 27

Scale with equal intervals between values but no true zero point (e.g., temperature in Celsius).

Question 28

Intervening variable

Answer 28

a hypothetical variable that explains the relationship between an independent variable and a dependent variable (mediator)

Question 29

Unit of analysis

Answer 29

the main entity or subject being studied in a research project

Question 30

Likert scale

Answer 30

a rating scale used in surveys to measure attitudes, opinions, or perceptions. ordered response options

Question 31

Measurement error

Answer 31

Difference between the true value and the observed score of a variable.

Question 32

Measurement validity

Answer 32

Degree to which a measure accurately captures the intended concept.

Question 33

Median

Answer 33

Middle value in an ordered distribution (dataset that has been arranged in ascending order)

Question 34

Mediating variable

Answer 34

Variable through which an independent variable (X) affects a dependent variable (Y).

Question 35

Missing data

Answer 35

When no data value is stored for the variable in an observation, potentially biasing results.

Question 36

Moderating variable

Answer 36

Variable that changes the strength or direction of the relationship between two variables.

Question 37

Multicollinearity

Answer 37

when two or more independent variables in a regression model are highly correlated, affecting the model's reliability

Question 38

Multiple regression

Answer 38

Statistical method estimating the relationship between one dependent variable and several independent variables.

Question 39

Nominal measurement

Answer 39

Categorical measurement without inherent order among categories (data that can only be categorized).

Question 40

Non-response

Answer 40

Failure of selected respondents to participate in a survey, possibly causing bias.

Question 41

Null hypothesis

Answer 41

Statement that no association (no statistical significance) exists between variables

Question 42

Operationalization

Answer 42

Defining how an abstract concept will be measured empirically (measurable observations).

Question 43

Ordinal measurement

Answer 43

Measurements with ordered categories but unequal intervals between them (Categorical, statistical data type)

Question 44

Outlier

Answer 44

a data point that differs significantly from other observations (can affect analysis results)

Question 45

p value

Answer 45

Probability of obtaining a result as extreme as observed, assuming the null hypothesis is true. (p value = probability value) (tells how likely that the data could have occurred under the null hypothesis)

Question 46

Panel study

Answer 46

Longitudinal study following the same individuals over time.