Quick Answer
The answer is `... | stats avg(response_time) by endpoint`. This search is correct because the `stats` command with the `avg()` function calculates the arithmetic mean of the `response_time` field, and the `by endpoint` clause groups those averages for each unique web endpoint, directly fulfilling the requirement to show average response time per endpoint over the past week. On the Splunk Core Certified User SPLK-1002 exam, this tests your understanding of the `stats` command’s syntax and its ability to aggregate data by a field—a core skill for creating reports. A common trap is confusing `avg()` with `sum()` or forgetting the `by` clause, which would produce a single overall average instead of per-endpoint values. Memory tip: think “AVG BY” as “average grouped by”—the field after `by` is your grouping category, and the field inside `avg()` is the numeric value you’re averaging.
This SPLK-1002 practice question tests your understanding of creating reports, dashboards and visualizations. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A user wants to create a report that shows the average response time for each web endpoint over the past week. The data has fields: endpoint, response_time. Which search correctly calculates the average?
... | stats avg(response_time) by endpoint
Correctly calculates average per endpoint.
... | stats mean(response_time) by endpoint
Why wrong: `mean` is not a valid function; use `avg`.
... | stats avg(response_time) by _time
Why wrong: Groups by time, not endpoint.
... | eval avg=sum(response_time)/count | stats values(avg) by endpoint
Why wrong: Overcomplicated and incorrect.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
... | stats avg(response_time) by endpoint
Option A is correct because the `stats avg(response_time) by endpoint` command calculates the average (mean) of the response_time field for each unique endpoint value. This directly meets the requirement of showing average response time per web endpoint over the past week, assuming the time range is set in the search bar or via an earliest/latest constraint.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
... | stats avg(response_time) by endpoint
Why this is correct
Correctly calculates average per endpoint.
Related concept
Read the scenario before looking for a memorised answer.
... | stats mean(response_time) by endpoint
Why it's wrong here
`mean` is not a valid function; use `avg`.
... | stats avg(response_time) by _time
Why it's wrong here
Groups by time, not endpoint.
... | eval avg=sum(response_time)/count | stats values(avg) by endpoint
Why it's wrong here
Overcomplicated and incorrect.
Common exam traps
Splunk often tests the distinction between `avg()` and `mean()` — `mean()` is not a valid SPL command, but candidates may confuse it with the statistical term or with SQL syntax, leading them to select Option B.
Detailed technical explanation
The `stats` command in SPL uses streaming and non-streaming aggregation functions; `avg()` is a non-streaming function that computes the arithmetic mean of numeric field values across events in each group defined by the `by` clause. Under the hood, Splunk calculates `sum(field)/count(field)` while automatically handling null values (they are ignored). In real-world scenarios, if response_time contains outliers (e.g., extremely high values from timeouts), the average can be skewed, so engineers often combine `avg()` with `perc()` or `median()` for a more robust view.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the SPLK-1002 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
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FAQ
Creating Reports, Dashboards and Visualizations — This question tests Creating Reports, Dashboards and Visualizations — Read the scenario before looking for a memorised answer..
The correct answer is: ... | stats avg(response_time) by endpoint — Option A is correct because the `stats avg(response_time) by endpoint` command calculates the average (mean) of the response_time field for each unique endpoint value. This directly meets the requirement of showing average response time per web endpoint over the past week, assuming the time range is set in the search bar or via an earliest/latest constraint.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This SPLK-1002 practice question is part of Courseiva's free Splunk certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SPLK-1002 exam.
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