12.1 Variables, Hypotheses, and Experimental Design
Key Takeaways
- GED Science experiment questions usually ask candidates to identify variables, judge whether a design is fair, or choose the conclusion supported by the results.
- The independent variable is the condition the investigator changes, while the dependent variable is the result that is measured.
- Controlled variables, repeated trials, and consistent measurement tools make an experiment more reliable.
- A strong hypothesis predicts a relationship that can be tested with data, not a vague opinion about what might happen.
- When results disagree or look unusual, GED Science questions often ask for the source of error or the design change that would reduce that error.
Read the Experiment Before the Answer Choices
GED Science is not mainly a memorization test. The official Science targets emphasize scientific reasoning in realistic situations, especially designing and interpreting experiments. When a question gives a procedure, slow down long enough to find the investigation question, the changed condition, the measured result, and the conditions that must stay the same.
A hypothesis is a testable prediction. It usually connects one variable to another: if the amount of salt in water increases, then bean seed germination will decrease. A weak hypothesis says only that salt affects seeds. A stronger hypothesis names a direction, a measurable result, and a comparison.
Variable Map
| Part of design | GED question wording | Example |
|---|---|---|
| Independent variable | What is changed or tested? | Amount of salt in each cup of water |
| Dependent variable | What is measured? | Number of seeds that sprout |
| Controlled variable | What is kept the same? | Seed type, water volume, light, soil, time |
| Control group | What gives a baseline? | Seeds watered with no salt added |
| Repeated trials | What reduces random error? | Testing several cups at each salt level |
Fair Comparison
A fair experiment changes only one major factor at a time. Suppose one group of plants receives fertilizer, more sunlight, and a larger pot while another group receives none of those changes. If the fertilized plants grow taller, the result does not prove fertilizer caused the growth. Sunlight or pot size could be responsible. Those extra differences are confounding variables.
GED questions often ask for the best improvement to a design. Good answers usually add a control group, increase the number of trials, keep conditions consistent, use a more precise measuring tool, or measure the dependent variable at regular intervals. Weak answers usually change several factors at once, use opinion instead of data, or collect data that does not match the hypothesis.
Experimental vs. Observational Designs
In an experiment, the investigator deliberately changes the independent variable. In an observational study, the investigator watches or records what already exists. A researcher can assign one set of identical batteries to a low-temperature chamber and another set to room temperature; that is experimental. A researcher who records battery failures from customers in different climates is doing an observational study.
Observational designs can reveal patterns, but they usually have more possible outside causes. The GED may ask whether a conclusion is too strong. If a study observes that people who live near parks report more exercise, it may support an association. It does not, by itself, prove the park caused the exercise unless the design controls other factors.
Design Checklist
Use this checklist on any GED Science experiment:
- Identify the question being tested.
- Name the independent and dependent variables.
- List the controlled variables that make the comparison fair.
- Check whether there is a control group or baseline.
- Decide whether the conclusion is limited to what the data show.
Error and Redesign
A source of error is anything that could make the measured result less accurate or less useful. A thermometer placed in direct sun may read too high. A balance not set to zero may make every mass too large. A small sample may exaggerate random differences.
When a GED item asks how to improve reliability, look for a change that directly addresses the weakness. If different students measured plant height using different rulers, use the same ruler or a standard method. If only one fish tank was tested at each water temperature, repeat the test with several tanks. The best design answer usually makes the data more comparable, not just more complicated.
A student tests whether light color affects algae growth. Four jars receive equal amounts of pond water and nutrients. Each jar is placed under a different color of light for 10 days, and the student measures the mass of algae at the end. What is the dependent variable?
A gardener wants to test whether fertilizer A helps tomato plants grow taller than no fertilizer. Which design gives the strongest evidence?