P.10 Making Conclusions
Purpose of a Conclusion
- Definition: A conclusion is a clear, concise statement summarizing what your results indicate about the research question or hypothesis.
- Relation to Hypothesis: It should directly address the initial question or hypothesis by interpreting the results in a straightforward way.
Writing Effective Conclusions
- Link to Results:
- Base your conclusion on patterns and trends observed in the data.
- Example: In the rennin experiment, you could conclude:
- “The greater the concentration of rennin, the shorter the time taken to reach the end-point, indicating that an increase in rennin concentration increases the rate of reaction.”
- Hypothesis Testing:
- If the experiment was testing a hypothesis, the conclusion should state whether the results support or do not support the hypothesis.
- Avoid Overstating:
- Do not claim to have “proved” the hypothesis; instead, indicate that results support or are consistent with the hypothesis, as multiple sets of results are generally needed for certainty.
Key Points for Writing a Conclusion
- Be Specific: Directly state the relationship or trend observed (e.g., “As X increases, Y decreases”).
- Avoid Certainty: Use cautious language to indicate support rather than proof (e.g., “The results suggest…”).
- Clarity and Focus: Make the conclusion concise, focused solely on the findings, and avoid introducing new information.
Example Conclusion Structure
Hypothesis | Conclusion Example |
---|---|
Increasing enzyme concentration increases rate | “Results support that higher enzyme concentration shortens reaction time, increasing reaction rate.” |
Temperature affects enzyme activity | “The results suggest that higher temperatures accelerate enzyme activity up to an optimum point.” |
Practical Tips
- Review Results: Summarize the observed trend in data clearly before formulating your conclusion.
- Address Limitations: Mention briefly if certain limitations may affect the strength of your conclusion.
- Stay Objective: Base conclusions strictly on the data without assumptions beyond the experiment’s scope.