Hypothesis and experimentation

A line graph clearly shows the trend between continuous variables. In exams choose the graph according to the data type.

An average is meaningful only for comparable values. In exams check that units and measured quantities are the same.

Soil type may affect growth and obscure the effect of the main independent variable. In exams identify confounding variables.

Similar results obtained by different people and at another location show reproducibility. In exams identify independent retesting.

Changing together does not prove causation unless other factors are controlled. In exams distinguish association from cause.

Temperature can directly affect enzyme activity so it must be controlled. In exams identify influencing factors in biological experiments.

Scientific evidence supports a hypothesis but does not establish it as final truth. In exams distinguish support from proof.

A wide spread may indicate inconsistent method or poor control. In exams examine the procedure before altering data.

An operational definition states exactly how a property will be measured. In exams link vague terms with measurable procedures.

An effect in the control group may indicate contamination or a procedural error. In exams check the integrity of the control.

Changes in apparatus or samples over time may create an effect linked to test order. In exams consider randomising the order.

Random selection helps make the sample more representative and reduces selection bias. In exams assess fairness in sampling.

Repetition and automatic timing reduce both random variation and reaction-time error. In exams consider method improvement together with repetition.

A controlled and repeated experiment provides stronger evidence of causation by reducing alternative explanations. In exams look for control and repetition.

Clear measurable variables make a hypothesis testable. In exams give operational definitions to vague terms.

A small sample and high variation reduce confidence in the conclusion. In exams state the limitations of the data clearly.

Many controlled and consistent opposite results provide strong evidence against a hypothesis. In exams consider both quantity and quality of evidence.

Without units it is unclear what quantity each number represents. In exams include the correct unit with each heading.

Less spread indicates closer repeated values and therefore greater precision. In exams connect data spread with precision.

The wall colour is unrelated to the variables in the hypothesis and provides no useful evidence. In exams identify relevant data.

Without a control group it is unclear whether the change was truly caused by the treatment. In exams understand the importance of a baseline comparison.

A complete method and conditions allow another person to repeat the same experiment. In exams connect a detailed procedure with reproducibility.

When there is no clear trend the limitation of the data should be acknowledged. In exams do not make a claim stronger than the evidence.

Removing contradictory results prevents an objective representation of evidence. In exams retain all valid results.

A strong investigation begins with a clear question and proceeds through controlled testing and analysis to conclusion and retesting. In exams remember the logical scientific sequence.