statistics phil 1

Epistemic objectivity

Knowledge reflects reality independently of observer beliefs, cultural context, and values.

Methodological objectivity

Use of standardized methods, replicable experiments, and quantification.

Procedural objectivity

Rules ensuring no personal bias, transparency, and reproducibility.

Empiricism

Knowledge comes from observation.

Verificationism

Theories must be verified by evidence.

Theory-ladenness

Observation is influenced by prior knowledge, theories, and expectations.

Thomas S. Kuhn

Philosopher who argued science progresses through paradigm shifts.

Paradigm

A framework including theories, methods, standards, and assumptions.

Epistemic values

Values such as accuracy, simplicity, and consistency.

Non-epistemic values

Values such as ethics, politics, and social impact.

Inductive risk

Risk of error when making conclusions under uncertainty.

Verification criterion

A statement is meaningful only if it can be empirically verified.

Demarcation problem

Problem of distinguishing science from pseudoscience.

Tautology

A statement true in all possible cases.

Law of excluded middle

Everything is either true or false.

Modus ponens

If A→B and A is true, then B is true.

Modus tollens

If A→B and not B, then not A.

Affirming the consequent

Invalid reasoning: If A→B and B, therefore A.

Denying the antecedent

Invalid reasoning: If A→B and not A, therefore not B.

Predicate logic

Logic that analyzes objects, properties, relationships, and quantifiers.

Universal quantifier

Means 'for all x'.

Existential quantifier

Means 'there exists at least one x'.

Induction

Reasoning from specific observations to general conclusions.

Uniformity of nature

Assumption that the future will resemble the past.

David Hume

Philosopher who argued induction cannot be logically justified.

Deduction

Reasoning from general laws to specific cases.

Deductive-nomological model

Scientific explanation as deduction from laws and conditions.

Karl Popper

Philosopher who proposed falsification as criterion of science.

Falsifiability

A theory is scientific only if it can be proven false.

Asymmetry principle

Many confirmations cannot prove a theory, but one counterexample can falsify it.

Auxiliary assumptions

Additional assumptions required to connect theory and prediction.

Duhem-Quine problem

Hypotheses cannot be tested in isolation.

Underdetermination

The same evidence can support multiple theories.

Confirmation bias

Preference for confirming evidence over disconfirming evidence.

Probabilistic theory

Theory predicting likelihoods rather than certainties.

Frequency interpretation of probability

Probability interpreted as long-run relative frequency.

Null hypothesis (H0)

Default assumption used in hypothesis testing.

Alternative hypothesis (H1)

Hypothesis proposing an effect or relationship.

P-value

Probability of observing data as extreme assuming H0 is true.

Type I error

Rejecting H0 when it is true.

Type II error

Failing to reject H0 when H0 is false.

Statistical threshold

Decision rule such as p < 0.05.

Normal science

Puzzle-solving within an accepted paradigm.

Scientific revolution

Replacement of one paradigm by another.

Incommensurability

Different paradigms cannot be directly compared using neutral standards.

Research program

Lakatos’ structured system of scientific work.

Hard core

Central assumptions of a research program.

Protective belt

Adjustable auxiliary assumptions surrounding the hard core.

Progressive research program

Program producing new successful predictions.

Degenerative research program

Program reacting to problems with ad hoc explanations.

Theory-data feedback loop

Theories guide observations and observations modify theories.

Operationalization

Defining abstract concepts using measurable indicators.

Independent variable

The variable treated as the cause.

Dependent variable

The variable treated as the effect.

Confounding variable

Variable influencing both X and Y, creating spurious correlation.

Counterfactual problem

Problem of knowing what would have happened without X.

Randomization

Method used to distribute confounders evenly.

Correlation

Two variables occurring together.

Causation

One variable producing change in another.