QCAA Agricultural Science EA key terms

The extent to which repeated measurements or trials under the same conditions give consistent results, allowing a researcher to trust that variation is not simply random error.

Whether a measurement or investigation actually tests what it claims to test, so conclusions drawn from the data genuinely answer the stated research question.

How close a measured value is to the true or accepted value, usually improved by calibrating instruments and reducing systematic error rather than by repeating trials.

How closely repeated measurements agree with one another, regardless of whether they are near the true value, and typically expressed through spread or standard deviation.

A consistent, directional deviation from the true value caused by faulty equipment, poor calibration or flawed technique, which shifts all readings in the same direction.

Unpredictable variation in measurements caused by environmental fluctuations, observer judgement or instrument limits, which scatters readings around a mean and is reduced by averaging repeats.

A factor deliberately held constant across treatments so that any observed change in the dependent variable can be attributed to the independent variable.

The factor the researcher deliberately manipulates or selects between treatments, such as irrigation rate or fertiliser concentration, to observe its effect.

The measured response of the organism or system, such as yield, growth rate or liveweight gain, which is recorded to assess the effect of the independent variable.

Repeating a treatment across multiple independent experimental units, such as separate plots or animals, so that natural variation can be separated from treatment effects.

Allocating experimental units to treatments by chance so that confounding factors are spread evenly across groups and do not bias the comparison.

An unmeasured factor that varies alongside the independent variable and can produce an apparent treatment effect that is not genuinely caused by the treatment.

A systematic distortion in sampling, measurement or reporting that pushes results away from the truth, often arising from non-random selection or observer expectations.

The number of independent observations or experimental units included in a study, which influences the precision of estimates and the power to detect real differences.

A statistic describing the typical spread of values around the mean, so a large value indicates highly variable data and greater uncertainty in the estimate.

The difference between a recorded value and the true value, arising from instrument resolution, technique, environmental conditions or observer interpretation.

Checking and adjusting an instrument against a known standard so that its readings correspond closely to true values before data collection begins.

A specific level or combination of the independent variable applied to experimental units, such as a particular fertiliser rate or stocking density.

A comparison group that receives no treatment or a standard practice, providing a baseline against which the effect of the manipulated variable is judged.

A data point that lies unusually far from the rest of the observations, which should be checked for measurement or recording error before being retained or excluded.

Non-numerical observations such as colour, behaviour, condition scores or farmer comments, which describe qualities rather than quantities and are often categorised for analysis.

Numerical measurements such as mass, length, yield or concentration that can be summarised statistically and compared between treatments.

The judgement, usually from a statistical test, that an observed difference is unlikely to have arisen by chance alone at a chosen probability threshold.

A testable, specific prediction about the relationship between variables that guides experimental design and can be supported or rejected by the collected data.

A focused, answerable question that frames an investigation, specifying the system, variables and context so that data collection and analysis stay directed.

Information produced by someone other than the investigator, such as scientific papers, industry reports or government statistics, used as evidence in a research investigation.

Data or evidence generated directly by the investigator or by the original researcher of a study, rather than interpreted secondhand through another author's summary.

Evaluation of a scientific article by independent experts before publication, which strengthens credibility but does not guarantee that findings are correct or applicable locally.

Acknowledging the source of information or ideas using a consistent referencing style, allowing readers to locate the original evidence and avoiding plagiarism.

Presenting another person's words, data or ideas as one's own without appropriate acknowledgement, which breaches academic integrity requirements for investigated and reported work.

Farming that meets current production needs while maintaining soil, water and biodiversity resources so that future productivity and profitability are not diminished.

The capacity of soil to function as a living system, supporting plant growth, cycling nutrients and water, and resisting degradation under agricultural use.

The decomposed plant and animal material in soil, which improves structure, water-holding capacity and nutrient supply and is a common indicator of soil condition.

The detachment and transport of soil by water or wind, often accelerated by bare ground, overgrazing or cultivation, reducing long-term productive capacity.

The proportion of soil surface protected by vegetation, crop residue or mulch, which reduces raindrop impact, runoff and erosion risk.

The movement of nutrients between soil, plants, animals and the atmosphere through processes such as decomposition, uptake, leaching and volatilisation.

The downward movement of dissolved nutrients, particularly nitrate, through the soil profile beyond the root zone, reducing efficiency and risking groundwater contamination.

Water that flows across the soil surface rather than infiltrating, carrying dissolved nutrients and sediment into waterways and reducing water available to crops.

A recognised, evidence-based farming technique or system, such as controlled traffic or precision application, adopted to reduce environmental impact while maintaining production.

Using sensor, satellite or variable-rate technology to apply inputs only where and when needed, improving efficiency and reducing off-site nutrient and chemical losses.

The variety of species, genetic variation and ecosystems present in an agricultural landscape, supporting pollination, pest control and resilience to environmental change.

A benefit that natural processes provide to agriculture, such as pollination, nutrient cycling, water filtration or pest suppression, often reduced when biodiversity declines.

A combined strategy using monitoring, biological control, cultural practices and targeted chemicals so that pesticide use is minimised and resistance risk is reduced.