When you look at a university profile on ComparED, the number you see is rarely the whole story. A figure like 80.4 for Overall Educational Experience at Australian Catholic University is a point estimate from the 2025 Student Experience Survey, and it comes with a 90% confidence interval of 79.8 to 81.0. That interval is not a footnote; it tells you how much the result could shift if the survey were repeated with a different sample of the same population. Reading it correctly is the difference between treating a small gap as meaningful and recognising that two universities may be statistically indistinguishable on a given measure.
The ComparED site, run by QILT, publishes survey results for Australian higher education institutions. The data you see there comes from national surveys rather than a census of every student. That distinction matters because it explains why confidence intervals exist at all. A sample is a subset, and any subset carries some uncertainty. The interval is the official way of expressing that uncertainty in the published tables.
What a 90% Confidence Interval Means
A 90% confidence interval means that if the same survey process were repeated many times, about 90% of the intervals calculated from those repeats would contain the true population value. It is not a statement that the true value has a 90% chance of falling inside this particular interval. That is a common misreading, and it is worth being precise about it.
Take the 2025 Student Experience Survey result for Bond University. The point estimate for Overall Educational Experience is 87.0, with a 90% confidence interval of 85.3 to 88.5. The interval is fairly narrow, which suggests the sample size was large enough to produce a reasonably precise estimate. Compare that with a smaller institution, such as Australian University of Theology, where the same measure shows 96.0 with an interval of 93.0 to 97.4. The interval is wider, reflecting greater uncertainty around the estimate.
When you compare two universities, the practical rule is to look at whether their intervals overlap. If the interval for one institution overlaps with the interval for another, you cannot confidently say that one is better than the other on that measure. The point estimates may differ, but the difference could be due to sampling variation rather than a real difference in student experience.
How to Read the Bracketed Numbers
On ComparED, the standard format for a survey result is a point estimate followed by a bracketed range. For example, the 2025 result for Deakin University on Learning Resources is 90.0 (89.5, 90.4). The first number is the percentage of positive responses. The numbers in brackets are the lower and upper bounds of the 90% confidence interval.
Some measures are marked with an asterisk. In the 2025 tables, Peer Engagement and Student Support and Services carry an asterisk for several institutions. The asterisk is a flag that the measure may have a different definition or a different set of respondents than the core measures. When you see it, check the ComparED help page for the exact wording before you draw conclusions.
A wider interval does not mean the result is wrong. It means the estimate is less precise. This often happens when the number of respondents from a particular institution or cohort is small. A narrow interval, by contrast, suggests a larger respondent base or a more consistent pattern of answers.
What n/a Means on ComparED
When a cell in a ComparED table shows n/a, it means the data is not available for that institution and measure. This is not the same as a zero score. It does not mean the institution performed poorly, and it does not mean the institution refused to participate. It simply means that no published estimate exists for that combination.
There are several reasons n/a can appear. The institution may not have had enough respondents to produce a reliable estimate. The measure may not apply to the institution’s cohort. Or the data may have been suppressed to protect respondent privacy. The ComparED help page on understanding the data explains the conventions used in the tables, and it is the right place to check when you encounter a value that does not look like a number.
If you are comparing institutions and one shows n/a, do not treat the missing cell as a zero. Treat it as an unknown. Your comparison should be based on the measures that are actually published for both institutions.
Why the Survey Is Not a Census
The QILT surveys are sample surveys, not full censuses. The Student Experience Survey collects responses from a large but still partial group of students. The published percentages are estimates of what the full population would say if every student had responded.
This has a practical consequence for how you use the data. A difference of one or two percentage points between two universities may fall within the margin of error. A difference of ten points, with non-overlapping intervals, is much more likely to reflect a genuine difference. The confidence interval is the tool that helps you make that judgement without over-reading small gaps.
How to Verify the Data Yourself
The primary source for all the figures on ComparED is QILT, the Quality Indicators for Learning and Teaching. The QILT website publishes the survey methodology, the data processing procedures, and the survey instruments. If you want to check a specific number, start with the QILT survey pages for the Student Experience Survey, the Graduate Outcomes Survey, the Graduate Outcomes Survey Longitudinal, and the Employer Satisfaction Survey.
The ComparED help page titled Understanding the Data is the most direct place to go for the site’s own explanation of how to interpret the tables. It covers the meaning of confidence intervals, the treatment of missing data, and the conventions used in the published results.
When you read a figure, always note which survey it came from, which year it covers, and which cohort it describes. A 2025 undergraduate result is not comparable to a 2024 postgraduate result, and a national figure is not an institutional figure. The ComparED tables are organised so that each row specifies the survey, the year, and the cohort. Keep that context in mind when you make comparisons.
Practical Rules for Comparing Universities
Start by identifying the measure you care about. If you are interested in teaching quality, look at Teaching Quality and Engagement. If you are interested in support services, look at Student Support and Services. Do not rely on a single overall score alone, because the component measures can tell a different story.
Next, compare the intervals rather than just the point estimates. If the intervals overlap, the difference is not reliable. If they do not overlap, the difference is more likely to be real. This is the single most useful habit you can develop when reading ComparED tables.
Finally, remember that survey results are one source of information. They reflect the experiences of students who responded in a particular year. They do not capture everything about a university, and they should be read alongside other evidence such as course content, location, cost, and your own priorities.
Where to Find the Official Sources
All the data on ComparED comes from QILT, which is the official Australian government initiative for quality indicators in higher education. The QILT website is the authoritative source for the survey methodology and the underlying data. The ComparED site is the public comparison tool that presents that data in a searchable format.
If you want to go deeper, the QILT data processing and procedures page explains how responses are weighted, how missing data is handled, and how the confidence intervals are calculated. That page is the technical reference for anyone who wants to understand the numbers at a more detailed level.
Common Questions About Reading ComparED
Does a wider interval mean the university is worse?
No. A wider interval means the estimate is less precise. It usually reflects a smaller respondent group or more varied responses. It does not indicate a lower quality of education.
Can I compare two universities if their intervals overlap?
You can compare them, but you should not conclude that one is better based on that measure alone. The overlap means the difference could be due to sampling variation. You would need additional evidence to support a claim that one is superior.
What should I do if a measure shows n/a?
Treat it as missing data, not as a zero. Look for the same measure in a different year or check whether the institution has published data for a related measure. Do not assume the institution is worse because a cell is empty.
Are the QILT 2025 results the most recent available?
The 2025 Student Experience Survey results are the most recent published at the time of writing. QILT releases new data on a regular cycle, so always check the QILT website for the latest release before making a decision.