Scientific Hypothesis Generation

Overview

Hypothesis generation is a systematic process for developing testable mechanistic explanations from observations. This knowhow covers the full cycle: from understanding a phenomenon through literature synthesis, generating competing hypotheses, evaluating hypothesis quality, designing experimental tests, and formulating testable predictions.

Key Concepts

1. Hypothesis vs Observation vs Prediction

• Observation: A factual statement about what was measured or seen (e.g., "Drug X reduces tumor size in mice")
• Hypothesis: A proposed mechanistic explanation for the observation (e.g., "Drug X inhibits angiogenesis via VEGF pathway blockade, reducing tumor nutrient supply")
• Prediction: A testable consequence of the hypothesis (e.g., "VEGF levels should decrease after Drug X treatment; tumors in VEGF-knockout mice should show no additional effect")

Good hypotheses are mechanistic (explain HOW/WHY), not descriptive (restate WHAT).

2. Hypothesis Quality Criteria