What experiment questions ask
An experiment passage usually follows the same pattern. It states a question or hypothesis, describes the procedure, and gives the results in a sentence, a table, or a graph. The questions that follow ask you to identify a part of the design, predict a result, find a weakness, or decide what the results show.
Read the passage once for the story: what was being tested and why. Then read it again, labeling each part on your scratch paper. Labeling keeps you from mixing up what was changed with what was measured, the most common error on these questions.
- Hypothesis: the testable prediction.
- Independent variable: what the researcher deliberately changes.
- Dependent variable: what is measured to see the effect.
- Controlled variables: conditions kept the same for every group.
- Control group: the group that does not get the treatment, used for comparison.
Finding the variables
Look for the one thing that differs between groups on purpose. That is the independent variable. Phrases such as “different amounts of,” “at four temperatures,” or “one group received” point to it. The dependent variable is the result the researcher records: a height, a time, a count, a temperature.
Everything else that could affect the result should be held constant. If the passage says all plants got the same soil, pot size, and light, those are controlled variables. A control group is different: it is a whole group that skips the treatment, such as plants that get no fertilizer, so the treated groups have something to be compared against.
Worked example
A student wants to know whether salt affects how fast ice melts. She places identical ice cubes on four plates in the same room and sprinkles 0 g, 1 g, 2 g, and 3 g of salt on them. She records the minutes until each cube is fully melted. Identify the independent variable, the dependent variable, the control group, and two controlled variables.
- Find what she changed on purpose: the amount of salt. That is the independent variable.
- Find what she measured: the minutes until each cube melts. That is the dependent variable.
- Find the group with no treatment: the plate with 0 g of salt is the control group.
- Find what stayed the same: the size of the ice cubes and the room temperature are controlled variables.
Hypotheses and predictions
A hypothesis is a statement that can be tested and could turn out to be wrong. GED questions often ask which hypothesis an experiment was designed to test, or which statement is a testable hypothesis. A good one names both variables and the expected relationship, often in an “if, then” form: “If more salt is added to ice, then the ice will melt faster.”
Rule out choices that are opinions (“Salt is the best way to treat icy sidewalks”), that cannot be measured, or that mention a variable the experiment never changes. To match a hypothesis to an experiment, check that its cause is the independent variable and its effect is the dependent variable.
Prediction questions ask what would happen under a new condition. Use the pattern in the results. If melting time dropped by about 4 minutes for each added gram of salt from 0 to 3 g, a prediction for 4 g should continue that trend. Be cautious about predictions far beyond the tested range, since patterns do not always continue.
Spotting design flaws
Some questions ask how an experiment could be improved or why its results may not be reliable. Check the design against a short list of common problems.
- More than one variable changed: if the salted cubes were also in a warmer spot, you cannot tell which change mattered.
- No control group: without an untreated group, there is nothing to compare the results with.
- Too small a sample: testing one plant or five people can give results that happen by chance.
- No repeated trials: running each condition several times and averaging makes results more trustworthy.
- Vague measurement: “the plant looked healthier” is weaker than a height measured in centimeters.
Worked example
A company tests a new sports drink. Ten volunteers drink it before a 2-mile run, and ten others drink water. The sports drink group runs in the cool morning, and the water group runs in the afternoon heat. The sports drink group has faster average times. What is the main flaw?
- Identify the intended independent variable: the type of drink.
- Look for a second difference between the groups: the time of day, and with it the temperature.
- Ask whether that difference could affect the dependent variable, run time: yes, heat usually slows runners down.
- Conclude: two variables changed at once, so the faster times cannot be credited to the drink. Both groups should run at the same time under the same conditions.
Choosing a supported conclusion
The correct conclusion is the one the results support, not the one that sounds most scientific or most complete. Stay inside the data. If a study tested tomato plants, a choice that makes a claim about all plants goes too far. If the results show a small difference in a single trial, a choice that says the treatment “proves” something is too strong.
Ask of each choice: does this data show it, and does it go beyond what was tested? Wrong answers are often true statements from general knowledge that the experiment did not measure. Another trap reverses the variables, such as saying melting time determined the amount of salt.
When results are in a table, compare the control group with each treatment group first. A conclusion about an effect needs a difference from the control, and a difference that grows steadily with the independent variable supports a stronger relationship than one that rises and falls with no pattern.
Frequently asked questions
- Do I need to know the science topic to answer experiment questions?
- Usually not. Most experiment questions can be answered from the passage alone by identifying what was changed, what was measured, and what the results show.
- What is the difference between a control group and controlled variables?
- A control group is a group that does not receive the treatment. Controlled variables are conditions, such as temperature or amount of water, that are kept the same for every group.
- Why do repeated trials matter?
- One trial can be thrown off by chance or a measurement mistake. Repeating each condition and averaging the results makes the findings more reliable.