Data Sufficiency

Some QR questions test whether you can determine what information is needed to answer a question — and whether the data set provides that information. While the UCAT does not have explicit "data sufficiency" questions in the way that some aptitude tests do, the concept is important because many QR questions include answer options like "Cannot be determined" or present scenarios where not all the information you might expect is available.

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What Is Data Sufficiency in QR?

Data sufficiency is about answering the question: "Do I have enough information to calculate the answer?"

In QR, this manifests in several ways:

Scenario 1: "Cannot Be Determined" as an Answer Option

Some questions include an option like "Cannot be determined" or "Not enough information." If the data set does not provide a value you need, this is the correct answer.

Scenario 2: Hidden Information

The data set may appear to lack information, but the answer can be derived from what is given. For example, if a table shows 4 of 5 categories and the total, you can calculate the 5th category by subtraction.

Scenario 3: Unnecessary Information

The data set may contain more information than you need. A table with 8 columns might be presented, but the question only requires data from 2 of them. Do not be distracted by irrelevant data.

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Identifying What Information You Need

Before looking at the data, determine what information the calculation requires.

Example: Percentage Question

Question: "What percentage of total revenue came from online sales?"

You need:

1. Online sales revenue
2. Total revenue

If the data provides both → You can answer.

If the data provides online sales but not total revenue (or a way to calculate it) → Cannot be determined.

Example: Speed Question

Question: "How long did the journey take?"

You need:

1. Distance
2. Speed

If the data provides distance and speed → You can answer (Time = Distance ÷ Speed).

If the data provides only distance → Cannot be determined.

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Common "Cannot Be Determined" Scenarios

Scenario 1: Missing Total

Data: A pie chart shows three segments: 30%, 25%, and 20%. The question asks for the value of the 30% segment.

Problem: No total is given. Without the total, 30% cannot be converted to a value. Cannot be determined.

However, if the question asks "What percentage of the budget is unaccounted for?", you can answer: 100% − 30% − 25% − 20% = 25%. No total is needed for this.

Scenario 2: Ambiguous Time Period

Data: A table shows monthly sales.

Question: "What were the annual sales?"

Problem: If the table shows only 6 months, you cannot determine the annual sales unless the question states you should assume the pattern continues.

Scenario 3: Missing Variable

Data: A table shows distance travelled by three cars.

Question: "Which car had the highest average speed?"

Problem: You need both distance and time. If time is not given, speed cannot be calculated. Cannot be determined.

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Deriving Missing Information

Sometimes the data appears insufficient, but the missing value can be calculated.

From Totals

If a table shows 4 values and a total, the 5th value = Total − Sum of the 4 known values.

From Percentages

If you know that categories represent 100% and you know all but one percentage, the missing percentage = 100% minus the others.

From Relationships

If "Revenue = Price × Quantity" and you know Revenue and Price, you can find Quantity.

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The "Not Enough Information" Decision Process

When you encounter a QR question, follow this process: