What Is P-Value?

Why It Matters for Supplement Brands

P-values are the most common metric used to determine whether a supplement ingredient has a statistically significant effect in a clinical trial. When evaluating studies for substantiation, understanding p-values helps you distinguish between meaningful findings and those that could be due to chance.

How It Works

In a typical supplement clinical trial:

1. **Null hypothesis**: There is no difference between the supplement group and placebo. 2. **P-value calculation**: After measuring outcomes, statistical tests calculate the probability of seeing the observed difference (or more extreme) if the null hypothesis were true. 3. **Significance threshold**: Conventionally set at p < 0.05 (5% probability of a false positive).

Interpretation: • p < 0.001 — Very strong evidence against the null hypothesis • p < 0.01 — Strong evidence • p < 0.05 — Statistically significant (standard threshold) • p ≥ 0.05 — Not statistically significant

Important: p-values do NOT tell you the size of the effect, only whether it's likely non-random. A small p-value with a tiny effect size may be statistically significant but not clinically meaningful.

Common Mistakes to Avoid

• ✗Equating statistical significance with clinical importance — a tiny effect can still be 'significant' with a large enough sample
• ✗Ignoring multiple comparison corrections — testing many outcomes increases false positive risk
• ✗P-hacking: running many analyses and only reporting the significant ones
• ✗Treating p = 0.06 as 'almost significant' or meaningfully different from p = 0.04
• ✗Not distinguishing between across-group significance (supplement vs. placebo) and within-group significance (before vs. after in the same group)

Related Terms

See It in Action

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