How can I reduce benchmark variability in my experiments?

How can I reduce benchmark variability in my experiments?

To reduce benchmark variability, ensure consistent experimental conditions, use a larger sample size, and control for external factors.

What specific factors should I control for?

You should control for environmental conditions, hardware differences, and data preprocessing methods to minimize variability.

Is there a recommended sample size for my experiments?

A larger sample size is generally better, but a common rule of thumb is at least 30 samples per group to achieve reliable results.

How can I ensure my data preprocessing is consistent?

Document your preprocessing steps, use automated scripts, and apply the same techniques across all datasets to maintain consistency.