Hypothesis and experimentation

The independent variable is the factor that the investigator deliberately changes to test its effect. In this hypothesis, the proposed cause is the amount of light: the experiment asks whether giving a plant more or less light changes its growth. Therefore, amount of light is the independent variable.

Plant height and number of leaves are possible measurements of growth, so they could be dependent variables, because they may respond to the light conditions. The amount of soil is a condition that should normally be kept constant if it is not being tested. Thus option A is correct. A useful rule is to ask, “What am I changing on purpose?” The answer identifies the independent variable.

The direct answer is C: if the amount of fertiliser increases, plant height will increase. A clear cause-and-effect hypothesis names the factor being changed and the result being measured. In option C, fertiliser amount is the proposed cause, or independent variable, and plant height is the proposed effect, or dependent variable. The statement can be tested by giving different fertiliser amounts to comparable plants and measuring their heights under the same light, water, soil, and time conditions. Option A is wrong because “beautiful” is subjective and does not identify a measurable cause or effect. Option B is too broad and vague: water may support life, but the amount, conditions, and measurable outcome are not specified. Option C is correct because it gives two clear variables and predicts their relationship. Option D is an observation about soil colour, not a cause-and-effect hypothesis. A hypothesis is a testable prediction, not merely an opinion. Memory cue: look for a changeable cause, a measurable effect, and often an if-then structure.

Changing both water and light makes the true cause of the result unclear. In exams keep one independent variable for a fair test.

A good hypothesis is based on prior knowledge and observations and is testable. In exams choose evidence-based statements.

Direct answer: Option B, the plant receiving no new fertiliser, is the control group. A control group is treated like the experimental group in all important ways except for the factor being tested. Here the tested factor is the new fertiliser, so the control receives ordinary conditions but no new fertiliser. Comparing growth in the two groups helps show whether any difference is associated with the new product. Option B is correct. Option A is not a control because double fertiliser is another treatment level. Option C is unsuitable because a different species has different natural growth, so species becomes a confounding factor. Option D is not a properly assigned group; choosing the tallest plant after growth introduces selection bias. Ideally plants should be similar and randomly assigned, with equal water, light, soil, time, and measurement methods. Memory cue: control means no tested treatment.

Keeping the amount of water the same ensures that only the effect of soap amount is tested. In exams control other influencing factors.

Accepting the actual data and reconsidering the hypothesis is scientific. In exams give priority to evidence.

The independent variable is the factor that a student changes deliberately during an investigation. The dependent variable is the result measured to see whether that change had an effect. In this investigation, the question asks whether different surfaces alter how far a ball rolls. The surface is therefore the factor selected and changed by the student.

Option A is correct because the type of surface may be changed, for example from a smooth surface to a rough one. The distance travelled is the measured outcome, so it is the dependent variable. The final position is another way of describing the outcome, and the measuring scale is equipment or a method, not the experimental factor. Other conditions, such as the ball and release method, should be kept constant.

The distance travelled by the ball is the measured outcome and therefore the dependent variable. In exams choose the measured result.

Calling a colour the most beautiful is a personal opinion and is not scientifically measurable. In exams identify subjective statements.

Identifying risks helps select precautions and reduces the chance of accidents. In exams match hazards with safety measures.

Repetition confirms results and reduces the effect of random error. In exams connect repetition with reliability.

The average of repeated measurements of the same quantity gives a representative value. In exams average only comparable values.

Growth is obtained from the difference between final and initial height. In exams subtract the initial value from the final value.

Seeds receiving the new chemical should be compared with untreated seeds. In exams identify the untreated baseline group.

The number of heartbeats per minute measures pulse rate. In exams choose an outcome that matches the hypothesis.

Pulse rate before exercise provides a basis for comparison. In exams identify the initial value as a control.

Seed size is the deliberately selected or changed factor and is the independent variable. In exams choose the factor acting as the cause.

Keeping the amount of water the same allows a fair test of seed size. In exams control other influencing factors.

A clear method allows the experiment to be repeated using the same steps. In exams write the complete procedure for reproducibility.

More samples reduce the effect of individual variation. In exams connect sample size with reliability.

An unusual value may result from error or real variation so it should be checked. In exams do not remove an outlier without evidence.

The conclusion is limited to the tested conditions and available data. In exams avoid overgeneralisation.

The exposed surface area is the independent variable that is deliberately changed. In exams identify the causal variable in the hypothesis.

The loss of mass in a fixed time indicates the amount of evaporation. In exams choose a measurable outcome.