Hypothesis and experimentation

Plant growth is the dependent variable because it is the outcome measured or observed when the duration of light is changed. Light duration is the independent variable because the student changes it. Factors such as soil type and amount of water should be kept constant for a fair test. Exam tip: the variable measured as the result of an experiment is the dependent variable.

In option A, temperature is deliberately changed and the time taken for sugar to dissolve is measured. Therefore, temperature is the independent variable, while dissolving time is the dependent variable. In option B, only plant height is observed; no factor being changed is clearly stated. Exam tip: The factor deliberately changed by the investigator is the independent variable.

The direct answer is C: the amount of salt. In a fair experiment, the independent variable is deliberately changed, the dependent variable is measured, and controlled variables are kept the same. Here the question asks how water temperature affects dissolving rate. Therefore temperature is the independent variable, dissolving rate or time is the measured outcome, and the amount of salt should remain constant. Step by step: change the water temperature; use the same quantity of salt each time; keep other relevant conditions, such as water volume and stirring, the same; measure how quickly the salt dissolves; compare the results. Option A is wrong as the controlled factor because water temperature is the independent variable being changed. Option B is wrong because dissolving time is part of the outcome being measured, not the factor held constant in this wording. Option C is correct because equal salt amounts make the comparison fair. Option D is wrong because a result is not a factor that can be controlled before measurement. Memory cue: change one factor, measure its effect, hold the important others constant.

A fair experiment is designed to test whether one factor causes a change in another factor. If several important factors are changed at the same time, the result cannot be linked confidently to any one of them. Changing only one main factor while keeping other relevant conditions constant makes the comparison meaningful. The changed factor is treated as the possible cause, and the measured response is then compared. Therefore option B is correct.

For example, if studying how temperature affects evaporation, the temperature may be changed, but the water volume, container, and observation time should remain the same. Changing the volume and temperature together would make the cause unclear. The purpose is not to make the experiment longer, reduce data, or save instruments. Repeated trials and careful measurements may still be needed, but controlling variables is what keeps the cause-and-effect relationship clear.

The second statement clearly includes light duration and a ten day period. This makes the outcome easier to measure.

A control group provides a baseline for comparison with the treated group. It helps identify the effect.

Direct answer: A, the plant without fertiliser. A control group provides a baseline for comparison and does not receive the treatment being tested. Step by step: keep plant type, water, light, soil, and other conditions as similar as possible; give fertiliser to the experimental group; give none to the control group; compare growth. A shows what happens without the fertiliser. B receives extra treatment, so it is experimental. C and D are selected by outcomes, not by experimental conditions, and choosing them can create bias. Memory cue: control means no tested treatment.

The rate of evaporation is correct because it is the measurable outcome that changes when temperature is varied; it is the dependent variable. Initial water volume, surface area, and room humidity can also affect evaporation, so they should be kept constant in a fair test. Exam tip: the effect predicted in a hypothesis is usually the dependent variable to be measured.

The direct answer is B: repeat the experiment several times using the same method. Reliability means that repeated testing gives consistent results. To improve it, perform several trials, follow the same instructions, measure carefully, and record every result rather than selecting only convenient values. Repetition helps reduce the influence of random or accidental errors, so the conclusion is based on more evidence. Option A is wrong because one trial cannot show whether its result is typical or accidental. Option B is correct because repeated trials under the same method allow comparison and reveal consistency. Option C is wrong and scientifically dishonest: recording only the desired result hides contrary evidence and creates bias rather than reliability. Option D is wrong because changing instruments can introduce new differences, making comparison less fair; a suitable calibrated instrument should be used consistently where possible. Repetition does not remove every systematic error, but it usually strengthens confidence in the result. Memory cue: same method, many trials, all results recorded.

A hypothesis suggests a possible relationship while a prediction gives the expected result from it. Both should be testable.

Direct answer: Option C, controlled variable, is the correct type. A controlled variable is a condition deliberately kept the same so that it does not confuse the comparison. Since every plant receives the same amount of water, water amount is controlled. The independent variable is the factor the investigator changes, such as fertiliser amount; the dependent variable is the measured response, such as plant height or number of leaves. Option A is wrong because water was not changed between groups. Option B is wrong because water amount is not the result being measured in the stated situation. Option C is correct because it is held constant. Option D is wrong because a conclusion is an interpretation of evidence, not a variable. Memory cue: changed = independent, measured = dependent, kept same = controlled.

Selecting only the data that support a hypothesis creates selection bias. The conclusion may then reflect the expected result rather than the actual evidence. Recording every result, using the same instrument, and repeating trials generally improve reliability. Exam tip: An unbiased experiment records results that both support and contradict the hypothesis.

For a valid comparison, the cloths should have the same size and the same amount of water at the start. Then any difference in drying rate can mainly be linked to sunlight versus shade. Option B is incorrect because light condition is the variable being changed. Exam tip: In a fair test, change only one variable and control the other important variables.

The direct answer is B: if the water amount increases, plant height gain over seven days will be greater. A scientific hypothesis should state the factor being changed, the result being measured, and enough conditions to make the test clear. Option B identifies water amount as the independent variable, plant height gain as the dependent outcome, and seven days as the measurement period. “Height gain” means the change in height from the beginning to the end, so it is more useful than simply saying the plant will be better. Option A is vague because “better” has no agreed measurement or time period. Option B is correct because both the outcome and time are clearly specified, although the exact water amounts and other controlled conditions should also be stated in a full experiment. Option C is vague and gives no measurable result. Option D uses “happy,” a human feeling that cannot be measured consistently in a plant. A strong test would measure initial and final height, calculate the increase, and compare groups fairly. Memory cue: a good hypothesis names what changes, what is measured, and when.

A stepwise procedure helps another person repeat the same experiment. This improves reproducibility.

Checking the instrument reduces measurement error. Conclusions should not be based on data from a faulty instrument.

A dependent variable is the outcome that is observed or measured in an experiment. For example, when studying the effect of water on plant growth, plant height is the dependent variable; measuring and recording it daily is therefore correct. Changing the amount of water changes the independent variable rather than measuring a result. Exam tip: Identify the variable recorded as the outcome to find the dependent variable.

Direct answer: B, record the unusual result and repeat the experiment. An unusual value may be caused by a recording mistake, equipment problem, uncontrolled condition, or genuine variation. Step by step: keep the value in the data record, check the procedure and apparatus, repeat measurements under controlled conditions, and compare repeated results before drawing a conclusion. B protects scientific honesty and tests reliability. A is wrong because deleting data hides evidence. C invents a value. D gives one value too much importance and ignores the rest of the evidence. Memory cue: unexpected data are checked, not erased.

One plant may not represent the whole group. More samples make a general conclusion more reliable.

The direct answer is B: soil may also affect the result. The investigation is supposed to test light, so the soil type should be kept the same in both plant groups. Step by step, light is the independent variable, plant growth is the dependent variable, and soil type is a possible controlled variable. If one group has different soil, that soil may change water retention, minerals, drainage or root growth. Then a difference in plant height cannot confidently be attributed to light alone. Option B is correct because soil becomes a confounding factor. Option A is wrong because adding another difference does not make the light effect clearer; it makes interpretation harder. Option C is wrong because different soils can cause different growth. Option D is wrong because the dependent variable, such as plant height, does not disappear; it may simply be affected by more than one factor. Memory cue: for a fair test, change one factor and keep other important conditions alike.

Repeatedly similar results improve repeatability and reliability. New evidence may still change the conclusion.

The direct answer is A, testing the effect of a new fertiliser on plant growth. A control group is a comparison group that does not receive the treatment being tested. Give the new fertiliser to one group of similar plants, but give no new fertiliser to another otherwise similar group. If both groups receive equal light, water, soil, and time, a difference in growth can be linked more confidently to the fertiliser. Option A needs this comparison because the question asks about an intervention. Option B, measuring one pencil, needs a measuring procedure, not a control group. Option C, observing water colour, does not involve a treatment comparison. Option D, measuring one stone’s mass, is also a direct measurement and has no experimental treatment. Thus A is correct. Memory cue: when asking “Does this treatment cause a change?”, include a no-treatment control.

The independent variable is the factor that the experimenter deliberately changes. Here, the student changes the amount of salt to observe its effect, so the amount of salt added is correct. The time taken for water to boil is the dependent variable because it is measured in response to the amount of salt. Exam tip: Identify what is changed first; that is the independent variable, while the measured result is the dependent variable.

A dependent variable is the outcome that is measured or observed in an experiment. Here, the time taken for water to reach boiling is recorded, so option C is the dependent variable. The amount of salt would usually be the independent variable, while the volume of water and container shape may be kept controlled. Exam tip: Identify the variable recorded as the result to find the dependent variable.

Data expressed in the same units can be compared directly. Convert different units into a common unit first.