HSC Science Extension key terms

The view that knowledge should be based on observation and experience rather than pure reasoning or tradition. Scientific claims are judged by evidence gathered from the world, not by authority alone.

A structured cycle of observing, forming questions, proposing explanations, gathering evidence and revising ideas. It is not a single fixed recipe but a set of disciplined practices for testing claims against reality.

A testable, specific statement predicting a relationship between variables. It must be phrased so that evidence could support or contradict it, and it usually follows from a broader research question.

A statement that there is no relationship or no difference between the variables being studied. Statistical tests assess how likely the observed data would be if this statement were true.

The property of a claim being open to being shown false by some possible observation. Claims that no evidence could ever contradict are generally excluded from empirical science.

A major change in the dominant framework of assumptions and methods within a field, often after accumulating anomalies undermine the old framework. It reshapes which questions and explanations are considered legitimate.

The broad agreement among specialists in a field about a body of evidence and its interpretation. It is provisional and can change, but it reflects accumulated scrutiny rather than mere majority opinion.

Evaluation of research by independent experts in the same field before publication or funding. Reviewers check methods, reasoning and claims, though the process does not guarantee correctness.

Repeating a study, ideally with new data or by other researchers, to see whether the findings hold. Successful replication strengthens confidence; failure prompts re-examination of the original claim.

The ability of others to repeat an analysis and obtain the same results when given the same data and methods. It depends on clear documentation of procedures, materials and decisions.

Reasoning from specific observations to a general conclusion, such as inferring a pattern from many cases. It supports but never strictly guarantees the general claim.

Reasoning from general premises to a specific conclusion, where the conclusion follows necessarily if the premises are true. It is used to derive testable predictions from theories.

A well-supported explanatory framework that accounts for many observations and has survived repeated testing. In science it is not a guess but the strongest kind of explanation available.

A focused, answerable question that defines what a study will investigate. A good one is specific, feasible and connected to existing knowledge or a recognised gap.

A critical survey of existing published work relevant to a research question. It identifies what is known, what is contested and where gaps remain, justifying the need for the proposed study.

The overall rationale and design of how a study will be conducted, including approach, sampling and analysis. It explains why chosen procedures can validly answer the research question.

The planned structure of a study, specifying variables, groups, timing and comparisons. It determines what conclusions can legitimately be drawn from the resulting data.

The factor that the researcher deliberately changes or selects in order to observe its effect. In observational studies it is the presumed explanatory factor rather than a manipulated one.

The factor that is measured or observed as the outcome of a study. Its values are expected to respond to changes in the independent variable.

A factor kept constant or accounted for so that it does not distort the relationship being studied. Careful control makes comparisons between conditions fairer.

A comparison group that does not receive the treatment or manipulation under investigation. It provides a baseline against which the effect in the experimental group can be judged.

Assigning participants or samples to groups by chance so that known and unknown influences are spread evenly. It reduces systematic bias in comparisons between groups.

A distortion that arises when the selected sample is not representative of the population of interest. It limits how far findings can be generalised beyond the sample studied.

A precise description of how a variable will be measured or manipulated in a particular study. It turns abstract concepts into observable quantities that others could replicate.

Formal review and permission from a committee before research involving humans, animals or sensitive data begins. It confirms risks, consent and welfare safeguards are acceptable.

Voluntary agreement by participants after being told the purpose, procedures, risks and their right to withdraw. It is a core requirement for ethical research with human participants.

Protecting participants so that their identity cannot be linked to the data they provide. It differs from confidentiality, which protects identity but may still allow the researcher to know it.

The accuracy, completeness and consistency of data throughout collection, storage and analysis. It requires honest recording, secure handling and resistance to selective reporting.

A systematic influence that pushes results or interpretations in a particular direction, away from the truth. Unlike random error, it does not cancel out with larger samples.

An unmeasured factor linked to both the independent and dependent variables, creating a misleading apparent relationship. Identifying and controlling confounders is central to sound causal inference.

A relationship where a change in one factor genuinely produces a change in another. It requires more than correlation, typically evidence of mechanism, temporality and control of confounders.

A statistical association in which two variables tend to vary together. Correlation alone cannot establish that one variable causes the other.

A statistical judgement about how unlikely the observed result would be if the null hypothesis were true. It indicates improbability under a model, not the importance or size of an effect.

A measure of how large a difference or relationship is, independent of sample size. It helps judge practical importance where statistical significance alone can mislead.

The range of possible error or doubt attached to a measurement or estimate. Reporting it honestly, often as intervals, shows how much confidence a result deserves.

The difference between a recorded value and the true value, arising from instruments, procedures or human judgement. It may be random or systematic and affects the reliability of conclusions.

The extent to which a study or measurement actually captures what it claims to. Threats include poorly defined variables, biased samples and confounding factors.

The consistency of a measurement or study when repeated under similar conditions. A reliable measure gives stable results, though it may still be measuring the wrong thing.

A judgement about what the evidence supports, stated with appropriate limits. Strong conclusions distinguish what was shown from what is merely suggested and acknowledge alternative explanations.

A reference acknowledging the source of an idea, fact or quotation. Correct citation lets readers verify claims and credits others' work, helping avoid plagiarism.

A structured written account of a study, typically including introduction, methods, results, discussion and references. It allows others to evaluate and build on the work.

A concise summary at the start of a report stating the aim, methods, key findings and implications. It lets readers decide quickly whether the full report is relevant to them.

The part of a report that interprets results, relates them to existing literature and acknowledges limitations. It separates what the data show from broader speculation or implication.

A constraint or weakness in a study's design, sample or analysis that restricts its conclusions. Stating limitations honestly strengthens credibility and guides future research.