What is the purpose of normalizing performance data before aggregation?

To make all response times equal

To account for varying load levels or test conditions

To convert data into a binary format

To delete all data that does not meet the target

A team ran a load test with two user groups: 'browsers' (80% of traffic) and 'checkout' (20% of traffic). The 95th percentile response time for browsers is 2 seconds, and for checkout it is 8 seconds. Management wants a single number to represent overall system performance. What is the most appropriate way to aggregate these results?

The lower of the two values (2 seconds)

Weighted average based on traffic mix (3.2 seconds)

Arithmetic mean of the two percentile values (5 seconds)

The higher of the two values (8 seconds)

A performance test of a login service produced response times in seconds: 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 12.0. The 12.0-second value came from a single user whose network dropped mid-request. The team wants to report a typical response time that is not skewed by this anomaly. Which aggregation should they use?

Arithmetic mean of all ten values

90th percentile of all ten values

Standard deviation of all ten values

A team is using a load testing tool that provides a built-in report with average, median, and 90th percentile response times. However, they need to calculate the 99th percentile, which is not in the report. What is the most efficient way to get this value?

Use the 90th percentile as an approximation

Use the average as an approximation

Use the median as an approximation

Export the raw data and use a spreadsheet to calculate the 99th percentile

Certified Tester Performance Testing

Domain 2Objective 4

Aggregating Results from Performance Testing CT-PT Practice Questions (Page 2)

Part of the Performance Measurement Fundamentals domain, which makes up ~28% of our current practice bank. ISTQB does not publish an official question count, but from its 90-minute exam (~35–60 total, ~10–17 in this domain), expect 2–3 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

7concepts

Questions 6–10

6foundation · easy
Which feature is typically built into load testing tools to aggregate results?
Select an answer first
7foundation · easy
What is the purpose of normalizing performance data before aggregation?
Select an answer first
8application · medium
A team ran a load test with two user groups: 'browsers' (80% of traffic) and 'checkout' (20% of traffic). The 95th percentile response time for browsers is 2 seconds, and for checkout it is 8 seconds. Management wants a single number to represent overall system performance. What is the most appropriate way to aggregate these results?
Select an answer first
9application · medium
A performance test of a login service produced response times in seconds: 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 12.0. The 12.0-second value came from a single user whose network dropped mid-request. The team wants to report a typical response time that is not skewed by this anomaly. Which aggregation should they use?
Select an answer first
10application · medium
A team is using a load testing tool that provides a built-in report with average, median, and 90th percentile response times. However, they need to calculate the 99th percentile, which is not in the report. What is the most efficient way to get this value?
Select an answer first

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Aggregating Results from Performance Testing CT-PT Practice Questions (Page 2)

Questions 6–10

Which feature is typically built into load testing tools to aggregate results?

What is the purpose of normalizing performance data before aggregation?

A team is using a load testing tool that provides a built-in report with average, median, and 90th percentile response times. However, they need to calculate the 99th percentile, which is not in the report. What is the most efficient way to get this value?

Keep studying — Performance Measurement Fundamentals