Terms

Question 1

The tendency to interpret new evidence as confirmation of one’s existing beliefs or theories.

Answer 1

Confirmation Bias

Question 2

A logical approach where you progress from general ideas to specific conclusions.

Answer 2

deductive reasoning

Question 3

A variety of methods of reasoning in which broad generalizations or principles are derived from a set of observations

Answer 3

Inductive reasoning

Question 4

Research proves null hypothesis, thus the research is not useful

Answer 4

Bias against negative results

Question 5

A variable that impacts the Dependent Variable, but does not impact other variables

Answer 5

independent variable

Question 6

A measured variable that is impacted by Independent Variables.

Answer 6

dependent variable

Question 7

The act of altering or manipulating research results to present a false or misleading representation of findings

Answer 7

Falsification

Question 8

The capacity for some proposition, statement, theory, or hypothesis to be proven wrong

Answer 8

falsifiability

Question 9

A claim, theory, or hypothesis that cannot be proven wrong or false

Answer 9

unfalsifiability

Question 10

Internal validity

Answer 10

the degree to which a study accurately reflects a causal relationship between the independent and dependent variables

Question 11

External Validity

Answer 11

Pertains to generalizability (if we did our study with a different sample, would we obtain the same result?)

Question 12

hypothetical scenarios that explore what would have happened if a certain factor or event had been different

Answer 12

Counterfactuals

Question 13

Experimenter controls who gets the treatment and who is in control group. Must have equal chance of being in either group

Answer 13

Random selection sampling

Question 14

Sampling techniques in which units are selected because they have characteristics that you need in your sample. In other words, units are selected “on purpose”.

Answer 14

purposive sampling

Question 15

The process by which participants are assigned by chance to separate groups that are given different treatments or other interventions

Answer 15

Randomization

Question 16

Used to categorize data into mutually exclusive categories or groups

Answer 16

Nominal variable

Question 17

Used to measure variables in a natural order, such as rating or ranking.

Answer 17

Ordinal Variable

Question 18

Used to measure variables with equal intervals between values.

Answer 18

Interval variable

Question 19

Allows for comparisons and computations such as ratios, percentages, and averages.

Answer 19

Ratio variable

Question 20

A statement of no effect or no difference between groups or variables, which researchers aim to disprove through statistical analysis

Answer 20

Null hypotheses for testing

Question 21

A single question that asks about two or more distinct issues or topics but only allows for one answer.

Answer 21

Double barrelled hypothesis

Question 22

Teleological arguments

Answer 22

Arguments that maintain that the earth, universe, etc, exist due to a purposeful creator or designer

Question 23

Functionalist arguments

Answer 23

Social structures and institutions exist and persist because they serve a purpose in maintaining social stability and order

Question 24

Dyads as a unit of analysis

Answer 24

Phenomena studied by collecting observations on dyads (pairs of countries)

Question 25

Mismatch in levels of analysis

Answer 25

When the theoretical framework, hypotheses, and data collection operate at different levels (individual, group, organizational, societal, etc.), leading to incorrect conclusions or invalid inferences.

Question 26

When you draw conclusions about individuals based solely on group-level data, assuming that what's true for a population is also true for each individual within that population.

Answer 26

Ecological fallacy

Question 27

A statistical method used to estimate the causal effect of an intervention or policy by comparing changes in outcomes between a treatment group and a control group, both before and after the intervention

Answer 27

Difference in difference

Question 28

A methodology that seeks to explain complex phenomena by breaking them down into simpler, more fundamental components or elements.

Answer 28

Reductionism

Question 29

Where you have one situation that leads to an effect, and another which does not, and the only difference is the presence of a single factor in the first situation, we can infer this factor as the cause of the effect.

Answer 29

Mill's Method of Difference

Question 30

Issue arising when multiple independent variables fully explain an outcome, making it difficult to identify which IV is responsible.

Answer 30

Overdetermination problem

Question 31

The number of independent values that are free to vary

Answer 31

Degrees of freedom

Question 32

Variables, other than the ones being studied, that can distort or mask the true relationship between the IVs and DVs, leading to misleading conclusions

Answer 32

confounding factors

Question 33

control variables

Answer 33

Variables that are held constant to isolate the effect of the IV on the DV

Question 34

When researchers choose their study sample based on the outcome they are trying to explain

Answer 34

Selection on the dependent variable

Question 35

Strengths of case studies

Answer 35

* Good for generating new hypotheses * Require less data than large n * Yields insight into unique events

Question 36

Weaknesses of case studies

Answer 36

* Overdetermination * Cases may not be representative * Can’t determine magnitude of IVs * Poor control for other variables * Omitted variable bias

Question 37

Strengths of large n statistics

Answer 37

* Generalizability * Identifying patterns and correlations * Replicability and transparency * Theory testing and model building

Question 38

Weaknesses of large n statistics

Answer 38

* Loss of context and nuance * Data availability and quality issues * Correlation vs causation problem * Arbitrary operationalization of variables * Overemphasis on statistical significance

Question 39

statistical significance

Answer 39

Indicates that the observed results are unlikely to have occurred by chance

Question 40

Type I error

Answer 40

When you reject the null hypothesis but it was actually true (false positive)

Question 41

Type II error

Answer 41

When you fail to reject the null hypothesis, but it was actually not true (false negative)

Question 42

False positive

Answer 42

Incorrectly detecting something that isn't there

Question 43

False negative

Answer 43

Failing to detect something that is actually there

Question 44

A number describing the likelihood of obtaining the observed data under the null hypothesis of a statistical test

Answer 44

p-value

Question 45

Omitted variable bias

Answer 45

When a statistical model fails to include one or more relevant variables

Question 46

What are historical analogies

Answer 46

Comparisons between past and present events to understand IR, predict outcomes, or justify policy decisions.

Question 47

What are misuses of historical analogy

Answer 47

* Oversimplification of complex events * Cherry-picking evidence * Ignoring structural differences * Emotional and cognitive bias

Question 48

What are uses of historical analogies

Answer 48

*Providing context and lessons * Theory development and testing * Identifying recurring patterns * Policy guidance

Question 49

Measuring net effect of program

Answer 49

Assessing the overall impact that a program has on its target population and beyond, by comparing outcomes with and without the program

Question 50

Occurs when the way participants or data are chosen for a study leads to a sample that doesn't accurately represent the target population

Answer 50

Selection effects

Question 51

Stochastic or design effects

Answer 51

Quantifies the extent to which the expected sampling error in a survey departs from the sampling error that can be expected under simple random sampling.

Question 52

Full coverage programs

Answer 52

Includes all relevant cases within a population of study. It aims for comprehensive analysis rather than selecting a subset of cases

Question 53

Partial coverage programs

Answer 53

Selects a subset of cases rather than analyzing the entire population. It is often used in small-N research,

Question 54

Used to indicate that a causal relationship has erroneously been assumed from a merely sequential one

Answer 54

Post hoc ergo propter hoc

Question 55

A logical fallacy where someone deflects criticism by accusing their accuser of the same behavior or wrongdoing, rather than addressing the original issue

Answer 55

tu quoque

Question 56

The technique or practice of responding to an accusation or difficult question by making a counteraccusation or raising a different issue.

Answer 56

Whataboutism

Question 57

When there is an accusation directed against a person rather than the position they are maintaining.

Answer 57

Ad hominem

Question 58

Points out that someone is in circumstances such that they are disposed to take a particular position

Answer 58

Ad hominem circumstantial

Question 59

A logical fallacy where you accept or reject an argument solely based on its origin or history, rather than evaluating the merits of the argument itself

Answer 59

Genetic fallacy

Question 60

An argument that claims an initial event or action will trigger a series of other events and lead to an extreme or undesirable outcome

Answer 60

Slippery slope

Question 61

A fallacy in which one modifies a prior claim in response to a counterexample by asserting the counterexample is excluded by definition.

Answer 61

No true Scottsman

Question 62

An argument in which the speaker deliberately ignores aspects that are unfavourable to their point of view.

Answer 62

Special pleading

Question 63

The phenomenon whereby a person is reluctant to abandon a strategy or course of action because they have invested heavily in it, even when it is clear that abandonment would be more beneficial.

Answer 63

Sunk cost fallacy

Question 64

A psychological phenomenon whereby the rate of uptake of beliefs, ideas, fads and trends increases with respect to the proportion of others who have already done so.

Answer 64

Bandwagon

Question 65

A logical fallacy that uses threats or intimidation to force someone to accept a conclusion, rather than relying on logic or evidence

Answer 65

Argument ad baculam

Question 66

When someone argues that because two things are similar in one way, they must be similar in other, unrelated ways, leading to a flawed conclusion

Answer 66

False analogy

Question 67

An argument or claim in which two completely opposing arguments appear to be logically equivalent when in fact they are not.

Answer 67

False equivalence

Question 68

A fallacy occurring when someone argues that a claim is true or false solely because there's no evidence for or against it, essentially claiming that the absence of evidence is evidence itself.

Answer 68

Appeal to ignorance

Question 69

A fallacy that presents an argument with only two options, when in reality more possibilities exist

Answer 69

False dichotomy

Question 70

Threats to inference or Threats to internal validity

Answer 70

Factors/explanations which we cannot rule out due to our research design (interchangeable terms)

Question 71

Can’t observe a change, because no pre-measurement (can’t attribute observed result to the treatment with any confidence)

Answer 71

Pre-experimental designs

Question 72

potentially anything that happened or changed between the two measurements could explain the second measurement

Answer 72

Pre-experimental designs

Question 73

Subsequent measures will tend to be closer to the average

Answer 73

Regression to the mean

Question 74

How do you fix threat from history impacting confounding factors?

Answer 74

Control groups (larger events affect both groups equally

Question 75

The test and control groups may not be equivalent, even if same scores on pre-measurement. They may be different on something unobserved which affects their predisposition to change

Answer 75

Quasi-experimental designs

Question 76

What is M a measurement of

Answer 76

The Dependent Variable (DV) at one point in time

Question 77

What is * a measurement of

Answer 77

The IVs or treatment or policy intervention

Question 78

How do you fix regression to mean in Quasi-experimental designs?

Answer 78

Multiple measurements

Question 79

Can Epidemiological studies establish a cause and effect relationship

Answer 79

No, we need data from a True Experiment to do that

Question 80

Why does the true experiment matter?

Answer 80

Because groups identical before treatment, any difference between the groups after the treatment, can only be due to the treatment (i.e. This controls for selection effects/bias)

Question 81

What is the only research design that can establish cause and effect relationships?

Answer 81

True Experiments

Question 82

What is process tracing

Answer 82

A case study technique to examine the causal mechanisms in a theory more closely

Question 83

A fallacy where anything less than 100% solution is unacceptable

Answer 83

Perfectionist fallacy