Metrics question

For a Google Search PM role, which is more important to focus on—mean or median—and why?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Statistical judgment: knowing when median is more informative than mean for a metric with outliers or skew, applied to Search.

Clarify the specific metric in question, such as latency, session length, or queries per user, since the right answer depends on it.
Note that Search usage is heavily skewed, since a small share of power users generates disproportionate query volume, pulling the mean up.
Argue for median as the headline metric, since it better represents the typical user experience and resists outlier distortion.
Note where mean still matters, such as revenue related metrics where total value, not typical value, is the concern.
Recommend tracking both, median for well being and mean or percentiles for capacity and revenue planning.

Ties the mean versus median choice to Search's actual skewed usage distribution rather than answering in the abstract.
Distinguishes user experience metrics favoring median from revenue and capacity metrics favoring mean or percentiles.
Recommends tracking both rather than picking one dogmatically, showing metric maturity.

Giving a one word answer without reasoning about the underlying distribution.
Ignoring that the right choice depends on which specific metric is being discussed.

Chapters of the AI PM course that teach what this question tests.