Experimental Design
Q3 on every AP Biology exam tests experimental design. This module covers the 7 required elements, the most-tested conceptual distinction (control group vs. controlled variables), hypothesis writing, and a fill-in FRQ template that works for any design question.
Where Experimental Design Appears
Experimental design questions appear in multiple locations on the exam. Q3 is the dedicated short FRQ, but design skills appear in MCQ and long FRQ as well.
| Location | How It Appears | What Is Tested |
|---|---|---|
| Q3 Short FRQ | "Design an experiment to test whether…" or "A researcher wants to determine if… Describe an experimental design." | Full experimental design: IV, DV, control, controlled variables, hypothesis, measurable outcome |
| Q1 / Q2 Long FRQ | Often the final sub-part: "Design a follow-up experiment to test…" | Extending an existing experimental context; one new IV manipulated while others held constant |
| MCQ Stimulus Sets | Questions about a described experiment: "What is the control group?" or "Which modification would improve this design?" | Identify variables, evaluate flaws, suggest improvements |
| Discrete MCQ | "Which experimental design best tests the hypothesis that…" | Choose the design that correctly isolates the variable of interest |
A valid experiment changes exactly one variable (the independent variable) while holding all other conditions constant, and measures a specific, quantifiable outcome (the dependent variable). Any design that changes more than one variable simultaneously cannot establish which change caused the observed effect. This is the fundamental logic AP readers test in every design question.
The 7 Elements of a Valid Experiment
Every experimental design question on the AP Biology exam scores points based on these seven elements. You do not need all seven for every question — check the point value and sub-part structure — but knowing all seven lets you write a complete design for any question.
Control Group vs. Controlled Variables
This is the single most commonly confused distinction in AP Biology experimental design. AP Readers specifically look for correct use of both terms.
A set of subjects that receives no treatment, a placebo, or the standard baseline condition. It exists as a reference point for comparison.
There is one control group per experiment (sometimes called "negative control"). A positive control (known to produce the expected result) may also be included.
- It is a group of organisms, cells, or samples
- It receives zero treatment or standard conditions
- You compare experimental group results to the control group
- Example: "Plants receiving 0 mg/L fertilizer"
The experimental conditions that are held constant across all groups — including the control group. They are not the same as the control group.
Controlled variables ensure that only the IV differs between groups, so any difference in the DV can be attributed to the IV alone.
- They are conditions, not groups of subjects
- They apply to ALL groups (experimental AND control)
- You must name specific variables, not say "everything else"
- Example: "Temperature (25°C), light intensity, soil type, watering volume"
Students write: "The control group is the group where temperature is kept constant." This is wrong. Temperature kept constant is a controlled variable. The control group is the set of plants/cells/organisms that receives no experimental treatment. A single experiment has one control group but many controlled variables.
| Scenario | Control Group | Controlled Variables (examples) |
|---|---|---|
| Testing effect of caffeine on heart rate in Daphnia | Daphnia in plain spring water (0 mg/L caffeine) | Water temperature, light level, Daphnia size, time of measurement |
| Testing effect of substrate concentration on enzyme activity | Enzyme solution with no substrate added (0 mM) | Temperature, pH, enzyme concentration, reaction time |
| Testing effect of antibiotic on bacterial growth | Bacteria on plates with no antibiotic (DMSO solvent only) | Bacterial strain, incubation temperature, growth medium, inoculum density |
Hypothesis Writing
AP Biology tests two types of hypotheses: the alternative hypothesis (your prediction) and the null hypothesis (used in statistical testing). Know when each is required.
States that there IS a relationship between IV and DV, and predicts the direction. Written as an if–then statement. Must be falsifiable and specific.
Format: "If [IV is manipulated in this way], then [DV will change in this direction], because [biological mechanism]."
Example: "If temperature increases from 20–40°C, then the rate of enzyme-catalyzed reactions will increase, because higher temperatures increase the kinetic energy of substrate molecules, increasing the frequency of productive collisions with the active site."
States that there is NO relationship between IV and DV — any observed difference is due to chance. Used as the starting assumption in statistical testing (chi-square, t-test). Rejected when p < 0.05.
Format: "[IV] has no effect on [DV]." OR "There is no statistically significant difference in [DV] between treatment groups."
Example: "Temperature has no effect on the rate of the enzyme-catalyzed reaction. Any observed differences between temperature groups are due to random variation."
• "State a hypothesis" or "Write a hypothesis" → write the alternative hypothesis (directional prediction with mechanism)
• "State a null hypothesis" → write the null hypothesis (no-effect statement)
• "The researcher uses a chi-square test. What is the null hypothesis?" → always the null hypothesis, stating observed frequencies do not differ from expected
• If not specified, default to the alternative hypothesis
FRQ Design Template
Use this fill-in template for any "design an experiment" sub-part. Each row corresponds to one or more scoring points on the AP rubric. Fill in the italicized placeholders with content specific to the question.
Worked Example — Template Applied
Hypothesis: If dwarf pea plants are treated with gibberellin, then their stem length will increase compared to untreated plants, because gibberellin promotes cell elongation in the stem by stimulating the loosening of cell walls and increasing vacuolar water uptake.
IV: Presence or absence of gibberellin, tested at: 0 μM GA (control), 10 μM GA, 50 μM GA, 100 μM GA.
DV: Stem length (cm), measured from the soil surface to the apical meristem using a ruler after 14 days.
Control group: Dwarf pea plants treated with distilled water only (0 μM GA). This controls for the effect of adding liquid to the plant independent of the hormone.
Controlled variables: Pot size and soil composition, watering volume (50 mL every 2 days), light intensity (16h/8h light/dark at 200 μmol photons/m²/s), temperature (22°C), plant age at start (7-day-old seedlings), pea cultivar (same dwarf variety throughout).
Replication: n = 10 plants per treatment group; experiment repeated twice.
Predicted result: Plants treated with higher GA concentrations will show greater stem elongation than control plants, with a dose-dependent increase in stem length.
Evaluating Existing Experimental Designs
Some Q3 questions (and Q1/Q2 sub-parts) ask you to evaluate a described design rather than create one. The same 7 elements are the checklist — identify which element is missing or flawed.
| Common Flaw | Why It’s a Problem | How to Fix It |
|---|---|---|
| No control group | Cannot establish baseline; impossible to attribute the change in DV to the IV | Add a group that receives no treatment or the zero level of the IV |
| Only one subject per group (n=1) | Cannot distinguish treatment effect from individual variation; results are not replicable | Increase sample size to n ≥ 3 per group |
| Multiple variables changed simultaneously | Impossible to determine which variable caused the observed outcome (confounding variables) | Change only the IV; hold all other conditions constant |
| DV is not quantifiable | "How well the plants grow" cannot be statistically analyzed or objectively compared | Replace with a specific measurable outcome: height (cm), mass (g), O₂ production rate (μmol/min) |
| Controlled variables not named | Reader cannot verify the design is valid; uncontrolled variables may have caused the result | Explicitly list at least 3 specific conditions held constant with values |
| No stated time frame | Unclear when measurements are taken; results from different time points are not comparable | Specify exact duration and measurement schedule: "after 14 days," "every 2 hours for 24 hours" |
Common Design Traps
- Confusing control group with controlled variables — the most common error. Control group = a set of subjects. Controlled variables = conditions kept constant. These are not the same thing.
- Changing two variables at once — e.g., increasing both temperature AND pH simultaneously. This creates a confounded design where neither variable can be said to cause the observed effect.
- Unmeasurable dependent variable — "observe how the organism responds" is not a DV. Every DV must produce a number with units.
- No control group for the solvent/vehicle — if a treatment is dissolved in DMSO, the control must receive DMSO only (not plain water), to control for DMSO’s own biological effects.
- Circular hypothesis — "If gibberellin is added, then gibberellin will cause elongation" restates the question without making a testable biological prediction. The because-clause must name the specific mechanism.
- Describing the expected result instead of the design — "The plants given more fertilizer will grow taller" describes an outcome, not a procedure. The design must describe what you will do, not what you expect to observe.
Practice Questions
A researcher wants to test whether a protein kinase inhibitor (Drug X) reduces the rate of cell proliferation in cancer cells. Which experimental design best tests this hypothesis?
- (A) Treat one flask of cancer cells with Drug X and count the cells after 48 hours
- (B) Treat cancer cells with Drug X at three concentrations and observe cell appearance under a microscope
- (C) Treat three groups of cancer cells with 0, 10, and 50 μM Drug X (dissolved in DMSO), with a DMSO-only control group, and measure cell number at 0 and 48 hours in each group
- (D) Treat cancer cells with Drug X and normal cells with no treatment and compare the results
A student designs an experiment to test the effect of soil pH on bean plant growth. She grows 5 plants in soil at pH 5, 5 plants in soil at pH 7, and 5 plants in soil at pH 9. She places pH 5 plants near a south-facing window, pH 7 plants under a grow light, and pH 9 plants in a shaded corner. Which statement best identifies the flaw in this design?
- (A) The sample size of 5 plants per group is too small to draw valid conclusions
- (B) Light intensity is not controlled across groups, so any difference in growth could be due to light rather than soil pH
- (C) The experiment should include more than three pH levels to be valid
- (D) Bean plants are not an appropriate organism for studying the effect of pH on plant growth
A student hypothesizes that increasing light intensity increases the rate of photosynthesis in aquatic plants. Design an experiment using Elodea (an aquatic plant) to test this hypothesis.