UCAT Decision Making Interpreting Information Questions: Method and Worked Examples

At TheUKCATPeople, I am Dr Akash, and interpreting information questions, sometimes called inference questions, are among the most winnable in Decision Making, because they reward one discipline above all: answering only from the evidence in front of you. You are given a passage, a table or a chart, and for each of five statements you decide whether it follows from that information alone. The marks are lost when students bring in outside knowledge or over-read a trend.

In the 2026 UCAT, Decision Making is 35 questions in 37 minutes, just over a minute per question, with a simple on-screen calculator and no negative marking (UCAT Consortium).

The UCAT Consortium describes Decision Making by its answer formats rather than publishing a fixed list of named question types. The type names used across preparation, including this one, come from the official UCAT question tutorials and practice materials.

This guide is the deep dive that sits under the Decision Making complete guide. It shares the five-statement yes or no format with syllogisms, so read both to tell the two apart cleanly.

What interpreting information questions test

These questions give you a stimulus, usually text, sometimes a table, chart or graph, and a set of conclusions. Your job is to judge whether each conclusion is supported by the specific evidence given. It is an evidence-bound inference task, not a general knowledge task and not a judgement task. If a statement needs a fact that is not in the stimulus, it does not follow, even if it is true in the real world.

Each interpreting information question uses the five-statement format, where you mark each statement Yes or No, so it is worth 2 marks, with partial credit for a partly correct response. The exact threshold for the partial mark is not published by the UCAT Consortium.

The method: how to answer interpreting information questions

1. Read the stimulus first, noting exact figures, units, dates and quantifier words such as all, some, most, only and at least.
2. Treat the passage or data as the entire universe of truth. Bring in no outside knowledge.
3. For each statement ask: must this be true given only this information? If it must, mark Yes. If it might be false, or needs an assumption or extra fact, mark No.
4. Check quantifiers and direction. Some does not support most; a rise in a rate does not support a rise in absolute numbers unless the base is known.
5. Read units and axes carefully: percentages against counts, per 1,000 against totals, cumulative against per period.
6. Answer all five statements. Partial credit means you should never leave the set blank, even on a triage flag.

Worked examples

Worked example 1: a text stimulus

A clinic saw 200 patients in June. Of these, 120 were female. Of the female patients, 30 were referred to a specialist. Of the male patients, 20 were referred to a specialist.

For each statement, decide whether it follows from the information given:

1. More than half of the patients seen in June were female.

Answer: Yes. 120 out of 200 is 60%, which is more than half.

2. Female patients were more likely than male patients to be referred to a specialist.

Answer: No. The female referral rate is 30 of 120, which is 25%, and the male rate is 20 of 80, which is also 25%. The rates are equal, not higher.

3. Exactly 50 patients in total were referred to a specialist.

Answer: Yes. 30 female plus 20 male referrals is 50.

4. Most patients seen in June were referred to a specialist.

Answer: No. 50 out of 200 is 25%, which is not most.

5. The clinic saw more male than female patients in June.

Answer: No. There were 80 male and 120 female patients.

Statement 2 is the rate trap: equal proportions can look unequal if you compare the raw counts (30 against 20) instead of the rates.

Worked example 2: a data table

The table shows disease rates and populations for two cities.

For each statement, decide whether it follows from the information given:

1. City A has a higher case rate than City B.

Answer: Yes. 400 per 100,000 is higher than 250 per 100,000.

2. City A has more cases in total than City B.

Answer: No. City A has 400 x 20 = 8,000 cases; City B has 250 x 50 = 12,500. City B has more.

3. City B has more than twice the population of City A.

Answer: Yes. 5,000,000 is more than twice 2,000,000.

4. If both cities had the same population, City A would report more cases.

Answer: Yes. City A has the higher rate, so at equal populations it would produce more cases.

5. The case rate in City B is exactly half that of City A.

Answer: No. 250 is 62.5% of 400, not 50%.

Statement 2 is the classic absolute-versus-rate trap. The city with the higher rate has fewer total cases because its population is much smaller.

Worked example 3: a bar chart

A bar chart shows the exam pass rate over four years: Year 1 = 60%, Year 2 = 72%, Year 3 = 68%, Year 4 = 80%.

For each statement, decide whether it follows from the information given:

1. The pass rate increased every year from Year 1 to Year 4.

Answer: No. It fell from 72% in Year 2 to 68% in Year 3.

2. The highest pass rate was in Year 4.

Answer: Yes. 80% is the highest of the four figures.

3. The pass rate in Year 4 was higher than in Year 1.

Answer: Yes. 80% is higher than 60%.

4. More students passed in Year 4 than in Year 1.

Answer: No. We are given rates, not the number of students in each year, so the absolute numbers cannot be compared.

5. The average pass rate across the four years was above 70%.

Answer: No. (60 + 72 + 68 + 80) divided by 4 is 70% exactly, which is not above 70%.

Statement 4 is the percentages-to-numbers trap, and statement 5 rewards a quick calculator check rather than an eyeball estimate.

Worked example 4: a study description

A study found that people who drank more coffee reported fewer hours of sleep. The study did not measure caffeine intake from other sources.

For each statement, decide whether it follows from the information given:

1. Drinking more coffee causes people to sleep less.

Answer: No. The study shows an association, not that one thing causes the other.

2. The study found an association between higher coffee consumption and fewer reported hours of sleep.

Answer: Yes. This is exactly what the stimulus states.

3. Caffeine is a stimulant that can disrupt sleep.

Answer: No. This is true in real life, but it is outside knowledge and is not supported by the stimulus.

4. People in the study who drank less coffee reported more hours of sleep on average.

Answer: Yes. The study reports the relationship as a consistent inverse one, so the lower-coffee group reported a higher average. This restates the finding rather than adding to it.

5. The study accounted for all sources of caffeine.

Answer: No. The stimulus states it did not measure caffeine from other sources.

Statement 3 is the single most common interpreting information error: true, but not supported by the passage.

Worked example 5: a text stimulus with no numbers

A hospital newsletter states that every doctor in the cardiology department has completed advanced life support training. It also states that some of the cardiology nurses have completed the same training, and that the department has more nurses than doctors.

For each statement, decide whether it follows from the information given:

1. Every member of the cardiology department has completed advanced life support training.

Answer: No. We are told every doctor and some nurses have, but nothing about the remaining nurses, so this cannot be concluded.

2. At least one cardiology nurse has completed the training.

Answer: Yes. The newsletter states some nurses have completed it, and in the UCAT some means more than one - so at least one has certainly completed it.

3. The department has more nurses than doctors.

Answer: Yes. This is stated directly.

4. Everyone who has completed the training is a doctor.

Answer: No. Some nurses have completed it too, so not everyone who has is a doctor.

5. There is a cardiology nurse who has not completed the training.

Answer: No. Some nurses have completed it, but some does not tell us the rest have not. It is possible that all the nurses have, so this does not follow.

This is the quantifier trap in words rather than numbers: some tells you about part of a group, never about the rest, and every doctor plus some nurses is not the same as every member.

Interpreting information, syllogisms and strongest argument compared

The five-statement yes or no format is shared with syllogisms, and students confuse the argument-based types too. This table keeps them apart.

For the argument-evaluation type, see the strongest argument guide. For the abstract-logic version of the yes or no format, see syllogisms.

Common traps that cost marks

• The outside-knowledge trap: a conclusion that is true in the real world but not supported by the stimulus. Mark it No.
• Quantifier over-reach: using some or a few evidence to justify all, most or none.
• Correlation treated as causation: the data shows an association, the conclusion claims a cause.
• Absolute versus relative: confusing a change in a rate or percentage with a change in the number of people.
• Reading the wrong row, series or axis on a table or chart.
• Reversed direction: increased against decreased, more likely against less likely.
• Mismatched time frames or units: a figure given per month set against one given per year, or a rate per 1,000 set against a raw count.

Many interpreting information questions carry a chart or table, so the same reading discipline from Quantitative Reasoning graphs and tables applies here. Use the timings guide to keep to just over a minute per question.

Once the method feels reliable, put it under time pressure in our data logic practice questions, and keep the rest of the section sharp with our free DM practice questions.

Test yourself

A survey of 150 patients found that 90 were satisfied with waiting times and 60 were satisfied with cleanliness, and 40 were satisfied with both. Decide whether each statement follows, then check the answers below.

1. Most patients were satisfied with waiting times.
2. Fifty patients were satisfied with waiting times but not with cleanliness.
3. Every patient was satisfied with at least one of the two aspects.

Answers

1. Yes. 90 of 150 is 60%, which is most.
2. Yes. 90 satisfied with waiting times minus the 40 satisfied with both leaves 50.
3. No. Satisfied with at least one is 90 + 60 − 40 = 110, so 40 patients were satisfied with neither.

Key Takeaway: Answer only from the evidence given. If a statement needs any outside fact or assumption, it does not follow, however true it sounds. Watch quantifiers, keep rates and absolute numbers separate, and always answer all five statements to bank the partial credit.