Writing a Testable Hypothesis
A good hypothesis:
- States a clear prediction about the relationship between the independent and dependent variables
- Is testable: you can design an experiment to support or refute it
- Includes a scientific reason (the "because" part)
Weak: "Temperature affects enzyme activity."
Strong: "As temperature increases from 20°C to 40°C, the rate of amylase activity will increase because enzyme molecules have more kinetic energy, leading to more frequent successful collisions with substrate molecules."
Notice the strong version specifies the direction of the effect, the range, and the scientific reasoning.
Writing a Valid Conclusion
A conclusion must:
- State the overall pattern or trend shown by the results: "As temperature increased, the rate of photosynthesis increased up to 35°C and then decreased"
- Quote specific data from your results: "The highest rate was 42 bubbles per minute at 35°C, compared to 12 bubbles per minute at 15°C"
- Explain the biology behind the pattern: "Higher temperatures increase kinetic energy of enzyme and substrate molecules. Above 35°C, the enzymes denature and the rate decreases"
- State whether the hypothesis is supported: "The results support the hypothesis that temperature increases enzyme activity up to an optimum, beyond which the rate decreases"
Do not make claims that go beyond your data. If you tested temperatures 20–50°C, do not conclude what happens at 60°C.
Identifying Anomalous Results
An anomalous result is one that does not fit the overall pattern. For example, if your results at 20, 25, 30, 35, and 40°C are 10, 18, 26, 14, 38, the value 14 at 35°C is anomalous because it breaks the upward trend.
How to handle anomalous results:
- Circle or identify the anomaly on the graph and do not include it in the line of best fit
- If possible, repeat the measurement at that value to check whether it was an error
- Suggest a possible cause (e.g. "the water bath may not have reached the correct temperature" or "the timing was started late")
- Do not simply ignore anomalies: acknowledge them and explain how they were dealt with