“Significant” means two different things in a research paper, and most of the confusion in a Results section comes down to which one you meant. Statistically, it means a result cleared a threshold — usually p<0.05 — against a null hypothesis. Everyday, it just means “important” or “worth mentioning.” English lets you use the same word for both. Your reader can’t always tell which one you’re using, and that’s the actual problem, not the word itself.
Here’s the line worth remembering: if a reviewer can’t tell whether “significant” means p<0.05 or just “notable,” that’s a sentence problem, not a results problem. You already have the finding. You just haven’t said which kind of significant it is.
The statistical meaning
In statistics, “significant” is a technical claim: the quantitative difference between two groups was large enough to satisfy the criteria of the test you ran. It needs a comparison, a test, and a threshold behind it. A clean example:
“There was a statistically significant difference between the experiment and control groups (P<0.05), leading us to reject our null hypothesis.”
Notice the sentence does three jobs at once: it names the comparison (experiment vs. control), it gives the threshold (P<0.05), and it says what that means for the hypothesis. That’s the version of “significant” that should never appear without a number attached, even if the number lives in a table rather than the sentence itself.
The everyday meaning
Outside your stats, “significant” just means important or relevant — no p-value required. “Iron ore is significant to Australia’s economy” isn’t a claim about a hypothesis test; it’s a claim about how much iron ore matters. Research findings can be “significant” to a policy debate the same way, purely on relevance, with no comparison group in sight.
Both uses are correct English. The trouble starts when a paper switches between them without telling the reader it’s switching.
Where it actually goes wrong
Picture a Discussion section that reports a statistically significant result in paragraph one, then writes “these are significant findings for the field” in paragraph three. A careful reviewer stops and asks: significant how? Statistically, like before — or just important, in the ordinary sense? If you mean the second one, say “important” or “notable” instead and save “significant” for the number. That single substitution removes the ambiguity for free.
There’s a second trap the tip doesn’t cover, and it’s the one that actually gets papers into trouble: statistically significant is not the same as actually significant. With a large enough sample, even a trivial, meaningless difference will clear P<0.05 — the test only tells you the difference probably isn’t zero, not that it’s big enough to matter. A 0.3% change in outcome across ten thousand participants can be “significant” and practically irrelevant at the same time. If your effect size is small, say so, and don’t let the p-value do the persuading on its own. Reviewers who work with statistics every day will notice if you do.
The fix, in one habit
Pair “significant” with “statistically” whenever you mean the test, every time, even when it feels repetitive by the fifth mention. Everywhere else, reach for “substantial,” “considerable,” or “notable” instead of bare “significant.” It costs you nothing and it means nobody has to guess which meaning you intended.
This is the kind of thing that’s easier to hear than read — Uni-edit’s writing tip on “significant” has two short videos walking through both meanings with more examples, on the University English Hub channel.
Part 2 goes further into the common mistakes writers make once they’ve got the basic split — worth five more minutes if this one raises questions of its own.
This is one word out of thousands in your manuscript, and it’s rarely the only one doing double duty. If you want the whole vocabulary checked for exactly this kind of ambiguity — words that are correct on their own but unclear in context — that’s what a full publication-quality edit is built to catch, alongside the sentence-level and structural issues a p-value can’t fix. If you’d rather work through the logic yourself first, the chapter “How to Master Similar Words in Your Research Paper” in How to Fix Your Academic English and Publish Your Research Faster covers this same kind of near-miss vocabulary in more depth.
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