Scientific Argumentation & Use of Evidence Flashcards

Evidence-based reasoning involves using empirical data to support or refute scientific hypotheses or claims, ensuring conclusions are grounded in factual information.

A hypothesis is a foundational element of the scientific method, guiding experiments and observations.

Empirical evidence is information gathered through observation or experimentation, serving as a critical foundation for validating scientific claims.

Both methods are fundamental for gathering data, with observation involving the careful monitoring of phenomena and experimentation involving controlled testing.

Reliability refers to the consistency and dependability of data, ensuring that results are replicable and accurate.

Inductive reasoning allows scientists to form general principles from specific data, although conclusions may not always be certain.

Theories are comprehensive explanations supported by extensive evidence, distinguishing them from hypotheses, which are preliminary conjectures.

Confirmation bias occurs when individuals favor information that confirms their pre-existing beliefs, potentially leading to skewed interpretations of data.

A larger sample size and proper controls help ensure data validity, reducing the impact of anomalies and confounding variables.

The strength of evidence is assessed based on the quality, quantity, and consistency of data, influencing the confidence in the scientific conclusion.

Correlation does not imply that changes in one variable cause changes in another; they merely change together.

An example of positive correlation is the relationship between height and weight in humans.

An example of negative correlation is the relationship between the number of hours spent studying and the number of errors made on a test.

Spurious correlations can arise due to chance or the presence of a confounding variable.

Causation implies a direct effect, while correlation merely indicates a relationship between variables.