Explain why the researchers used data from ten trails and averaged them, rather than data from a single trail ?

Researchers often use data from multiple trials and average them to reduce the impact of random errors and outliers on the results. When a single trial is conducted, there's a higher possibility that the results may not be representative due to random variations that can occur due to many factors such as environmental conditions, measurement errors, or unexpected disturbances.

By conducting multiple trials and averaging the results, researchers can:

1. Increase Reliability: Averaging data from multiple trials tends to cancel out random errors. If an error makes the result of one trial too high, and another makes the next trial too low, these errors can balance out over many trials.

2. Improve Accuracy: The average of several trials is more likely to be closer to the true value than any single measurement.

3. Identify Outliers: Outlying results, which may be due to experimental anomalies, become more apparent when multiple trials are conducted.

4. Assess Consistency: If the results of the trials are close to each other, it provides confidence that the experiment is consistent and repeatable.

5. Refine Experimental Technique: Multiple trials allow researchers to refine their experimental techniques, identifying sources of error that can be mitigated in future trials.

6. Statistical Analysis: It provides a larger set of data that can be analyzed statistically. Statistical tests often require a certain amount of data to be valid and multiple trials can provide this.