The Ipsos Ireland example
Consider the Ipsos LGBT+ Pride 2025 survey.
Ipsos interviewed approximately 500 people in Ireland using its Global Advisor online platform. Ipsos then reported its findings as percentages of the Irish respondents.
When 500 People Become “Ireland”: The Numbers Behind Opinion Polls
How much can a survey of a few hundred people really tell us about millions?
We see percentages everywhere.
78% agree.
64% support it.
72% believe this.
The numbers look precise. They look scientific. They appear to tell us exactly what “the public” thinks.
But there is an important question that ordinary members of the public should always ask:
Who exactly was asked?
A survey does not normally ask every person in a country. Instead, researchers select a sample and use the responses to estimate the views of a much larger population.
That approach can be perfectly legitimate when the sampling methodology is appropriate.
But the limitations of the sample matter enormously.
The Ipsos Ireland example
Consider the Ipsos LGBT+ Pride 2025 survey.
Ipsos interviewed approximately 500 people in Ireland using its Global Advisor online platform. Ipsos then reported its findings as percentages of the Irish respondents.
The important part is what Ipsos itself says about its Irish sample.
Ipsos states that samples in Ireland are “more urban, more educated, and/or more affluent than the general population.”
It then says that the results for countries including Ireland should be viewed as reflecting the views of the more “connected” segment of the population.
That qualification deserves attention.
Because there is a considerable difference between:
“78% of the 500 people surveyed agreed with this statement.”
and:
“78% of Irish people agree with this statement.”
Those two sentences are not the same thing.
But don’t polls only need a small sample?
This is where polling methodology becomes interesting.
A sample does not necessarily have to contain millions of people to estimate the views of millions.
A properly designed sample can produce useful estimates from a relatively small number of respondents.
But sample size isn’t the only issue.
Who is included?
Who isn’t included?
How were respondents recruited?
Are they representative of the population being discussed?
What weighting was applied?
What questions were they actually asked?
And what assumptions were made when the results were extrapolated?
Ipsos itself recognises this distinction. In the Pride 2025 methodology, it says its Irish sample has demographic limitations and should be regarded as reflecting the more “connected” segment of the population. It also says the data were weighted to demographic profiles based on census information.
So weighting can attempt to correct differences between a sample and a population.
But weighting doesn’t magically turn 500 people into 5 million people.
It is a statistical adjustment, not additional respondents.
The mysterious decimal point
There is another psychological effect worth considering.
When we see:
78%
our brain tends to interpret it as a precise measurement.
But the number actually comes from people answering a particular question under particular circumstances.
Ipsos itself says that for an online poll with N=500, its stated credibility interval is approximately ±5 percentage points.
That means a result reported as 78% should not be interpreted as though someone counted exactly 78% of the entire Irish population.
It is an estimate derived from the survey methodology.
And there is another complication: Ipsos describes these online polls as non-probability-based.
That is a very important piece of information for anyone reading the headline.
The question matters too
There is also a danger in turning a specific survey question into a much broader statement.
For example, asking people whether transgender people should be protected from discrimination in employment, housing and access to businesses is not the same question as asking whether they support every aspect of transgender policy.
The wording of a question determines what the resulting percentage actually means.
A survey cannot legitimately answer a question that it never asked.
Numbers need context
This isn’t an argument that all surveys are fake.
Nor is it an argument that statistical research has no value.
Quite the opposite.
Good quantitative research can tell us enormously useful things about populations.
But statistics need context, methodology and transparency.
A responsible reader should be able to ask:
What population does this percentage actually describe?
How were the respondents selected?
How many people were questioned?
Was the sample probability-based or non-probability-based?
Was it representative of the population?
What weighting was applied?
What exactly was the question?
What uncertainty surrounds the result?
These aren’t awkward questions.
They’re basic questions about research methodology.
The public deserves to know
Most people aren’t professional statisticians.
They shouldn’t have to be.
When a headline announces that “78% of Irish people” believe something, the average reader is entitled to understand whether that means 78% of the entire population, 78% of a representative sample, or 78% of a particular online panel.
Those distinctions can become particularly important when polling results are subsequently repeated by newspapers, television stations, radio programmes and social media.
One survey becomes a headline.
The headline becomes another news story.
The news story becomes another reference.
And eventually the original methodology can disappear while the percentage remains.
The number survives. The qualification gets lost.
That is why the public should not simply ask:
“What percentage did the poll produce?”
We should also ask:
“How did they get the number?”
Because a percentage without its methodology is only half a story.
And when that percentage is being used to describe the opinions of an entire country, the other half matters.
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