📖 Overview

Use this Correlation Coefficient Calculator (Matthews) to run the core math with transparent assumptions and quick interpretation-ready results.

🧪 Example Scenarios

Use these default and higher-pressure example inputs to explore how sensitive this calculator is before using your real numbers.

ExampleExample: TP 88, TN 170, FP 12, and FN 20 gives an MCC of about 0.79.
InputBase CaseHigher Pressure Case
True Positives88101.2
True Negatives170195.5
False Positives1213.8
False Negatives2023

⚙️ How It Works

This calculator applies a direct math model based on the inputs above.

💡This calculator is scenario-based. Better input quality leads to better decision quality.

Quick Reference

InputExample Value
True Positives88
True Negatives170
False Positives12
False Negatives20

When To Use This

  • Use this tool when you need a fast decision during active planning or execution.
  • Use this before committing money, time, or tradeoffs that are hard to reverse.
  • Use this to compare options using the same assumptions across scenarios.

Edge Cases To Watch

  • Results can be misleading if key inputs are missing, stale, or unrealistic.
  • Very small or very large values may amplify rounding effects and interpretation risk.
  • If assumptions change mid-decision, recalculate before acting.

Common Mistakes

  • Looking only at accuracy on imbalanced data.
  • Swapping false positives and false negatives.
  • Treating MCC as a percentage instead of a -1 to 1 score.

Practical Tips

💡 Validate units before comparing scenarios.
💡 Run multiple values to understand sensitivity.
💡 Use outputs as estimates, not guarantees.

Frequently Asked Questions

❓ What is a good MCC score?

MCC ranges from -1 to 1. Values closer to 1 indicate stronger classification performance.

❓ Why use MCC instead of accuracy?

MCC handles class imbalance better because it uses TP, TN, FP, and FN together.

❓ Can MCC be negative?

Yes. A negative MCC means predictions are worse than random in the opposite direction.

❓ Is this output exact?

It is a fast estimate based on provided inputs and model assumptions.

❓ Can I compare different scenarios?

Yes, this tool is designed for quick side-by-side checks.