Basic Science Research
High-Yield Summary
- Basic science research gives the experimenter the most control over variables — the independent variable is manipulated, the dependent variable is measured.
- Positive controls confirm the setup can detect an effect; negative controls confirm no effect occurs without the independent variable.
- Causality requires the outcome be directly attributable to the manipulated variable, not to confounding factors.
- Systematic error skews results consistently in one direction; random error is unpredictable and averages out with a larger sample.
- Accuracy = closeness to the true value; precision = consistency between measurements — a result can be one without the other.
Core Variables
- Independent variable
- The factor the experimenter changes or manipulates.
- Dependent variable
- The outcome being measured.
- Causality
- The if-then relationship: the change in the dependent variable must be directly attributable to the independent variable, not to interference from other factors.
Positive vs. Negative Controls
| Positive control | Negative control |
|---|---|
| Confirms the experiment CAN produce a measurable effect | Confirms there is NO effect when the independent variable is absent |
| e.g., plants grown under known-good white light | e.g., plants grown in complete darkness |
Systematic vs. Random Error
| Systematic error | Random error |
|---|---|
| Consistent inaccuracy that skews results in one direction (e.g., a miscalibrated ruler) | Unpredictable fluctuation (e.g., day-to-day environmental variation) |
| Caused by a flaw in the experimental setup | Less concerning with a large sample — effects average out over trials |
Precision vs. Accuracy — the Target Analogy
- Accurate + precise (ideal)
- Measurements tightly clustered right on the true value.
- Accurate, not precise
- Measurements scattered around the true value — close on average, but inconsistent.
- Precise, not accurate
- Measurements tightly clustered but far from the true value — consistent, but systematically wrong (often from systematic error).
- Neither accurate nor precise
- Measurements scattered and far from the true value.
Common MCAT Trap
- Precise ≠ accurate: tightly clustered measurements can still be tightly clustered around the WRONG value — that's a hallmark of systematic error, not random error.
- Random error isn't a design flaw to fix — it's inherent noise that a bigger sample size dilutes; systematic error requires fixing the setup itself.
Quick Recall
Every trial reads exactly 8.5 cm, but the true value is 10 cm. Precise, accurate, both, or neither?
A group of plants is grown in total darkness to confirm no growth effect occurs without light. Positive or negative control?