Hypothesis and experimentation

A tilted cylinder affects the correct reading of liquid level. In exams keep the instrument on a level surface.

A reading taken before stabilisation may not show the true temperature. In exams wait until the value becomes stable.

A valid numerical comparison can be made only after conversion to a common unit. In exams standardise units before comparison.

Immediate organised recording keeps data clear and reliable. In exams include headings and units.

The direct answer is C, confirmation bias. A fair investigation requires recording every relevant result, including results that do not support the hypothesis. If a student chooses only favourable results, the evidence becomes incomplete and the conclusion is likely to be unfair. That habit is called confirmation bias: accepting information that agrees with an existing belief and ignoring information that disagrees. Option A, random error, is an unpredictable variation in measurements, not selective recording. Option B, measurement limit, is the smallest amount an instrument can reliably show and does not describe choosing results. Option C is correct because the student selected evidence to confirm the hypothesis. Option D, a controlled test, is a fair design in which important conditions are kept constant; it is the opposite of this problem. Exam reminder: never hide an unexpected result; record it, check it, and discuss it honestly.

Rinsing removes the chemical and the teacher can provide suitable help. In exams follow safety instructions.

Normal room temperature can provide a baseline condition for comparison. In exams choose the group under normal conditions.

Different species may germinate differently so the comparison will not remain fair. In exams keep starting materials the same.

This statement gives a testable prediction linking the changed and measured variables. In exams identify a clear if-then relationship.

Widely different results may indicate a problem with method or measurement. In exams check and repeat when data is inconsistent.

Similar results obtained by different people using the same method show reproducibility. In exams identify independent verification.

Similar results across several trials increase reliability. In exams look for both repetition and consistency.

Keeping the wire material and thickness the same allows a fair test of length. In exams control other factors.

Scientific data may support a hypothesis but does not prove it as an absolute final truth. In exams distinguish support from proof.

Change in height over a fixed period provides a clear measure of growth. In exams define vague qualities operationally.

Plant height is measured as the effect of the changed water amount. In exams identify the outcome as the dependent variable.

Different durations may affect the result and become an additional variable. In exams keep the test duration constant.

Incorrect calibration can shift all measurements away from the true value. In exams connect calibration with accuracy.

During data analysis patterns and meaning in the results are examined. In exams place it before the conclusion.

Placing the independent variable in the first column clearly links each changed value with the result. In exams organise tables logically.

This title clearly states both the independent and dependent variables. In exams state the tested relationship in the title.

Several trials help check consistency and obtain a representative average. In exams identify the benefit of repetition.

A scientific investigation begins with a question and hypothesis then proceeds through variables and method to data and conclusion. In exams remember the logical sequence.

A good experiment is based on fair testing control safety and repeatability. In exams identify these qualities together.

Keeping the cloth size and initial amount of water the same ensures that only the effect of airflow is tested. In exams control other influencing factors.