Write a possible conclusion to your hypothesis in part (a).
How to approach this question
1. **Recall the SRCC value**: The calculated value is 0.89.
2. **Interpret the SRCC value**:
* The value is positive, so there is a positive correlation.
* The value is close to +1 (a perfect positive correlation). A value of 0.89 is considered a **strong** positive correlation.
3. **Relate this back to the hypothesis**: The hypothesis in part (a) was that there would be a positive correlation.
4. **Formulate the conclusion**: State the strength and direction of the correlation found, and state that this supports the original hypothesis. For example: "The result of 0.89 shows a strong positive correlation, which supports the hypothesis."
Full Answer
The SRCC value of 0.89 indicates a strong positive correlation. This supports the hypothesis that there is a positive correlation between resting heart rate and finishing position number.
To write a conclusion, we must interpret the calculated Spearman's Rank Correlation Coefficient (SRCC) of 0.89 in the context of the investigation.
1. **Strength and Direction**: An SRCC value can range from -1 to +1.
* A value of +0.89 is positive and close to +1. This indicates a **strong positive correlation**.
2. **Context**: This strong positive correlation is between resting heart rate and finishing position number. This means that competitors with a higher resting heart rate tended to have a higher finishing position number (i.e., they finished the race more slowly).
3. **Link to Hypothesis**: The original hypothesis was that there would be a positive correlation. The result strongly supports this.
**Conclusion**: The SRCC value of 0.89 indicates a strong positive correlation between resting heart rate and finishing position. This supports the initial hypothesis.
Common mistakes
✗ Just stating "positive correlation" without mentioning the strength (strong).
✗ Not linking the conclusion back to the context of the variables (heart rate and finishing position).
✗ Stating that correlation proves causation (e.g., "a high heart rate *causes* a bad finish"). Correlation does not imply causation.
Expert