High Hypothesis Testing Question 151 of 220

What is false discovery rate control, such as Benjamini-Hochberg?

Data Science track · Speak this in 60–90 seconds · Faridabad & Delhi NCR

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Simple meaning

FDR is the expected share of rejected nulls that are false discoveries.

WHY — Hypothesis Testing instead of guessing?

Why interviewers care about Hypothesis Testing:

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people who only read docs from people who shipped.

Keep it short, concrete,

and tied to Data Science work.

Stay structured

Name the idea, why it exists, then one short example.

Close cleanly

End with when you use it and one common pitfall.

STEPS — What happens step by step?

Before you speak the answer, walk the interviewer through these steps:

1
FDR is the expected
share of rejected nulls that are false discoveries.
2
Benjamini-Hochberg ranks p-values and
uses a linear threshold so that, under independence or certain dependence, FDR is bounded by q.
3
It is a better
default than Bonferroni when you are screening many segments and can tolerate some false leads.
4
Give an example
One tiny concrete case you can say aloud.
5
Common mistake
What juniors usually get wrong.
6
Close
When you pick this over the alternative.

EXAMPLE — See it in action

Here's a short line you can speak, broken into clear beats:

Say this line

“Benjamini-Hochberg ranks p-values and uses a linear threshold so that, under ind”

Break into beats

BenjaminiHochbergrankspvaluesand

Speaking order

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Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

Key takeaway

FDR is the expected share of rejected nulls that are false discoveries. Benjamini-Hochberg ranks p-values and uses a linear threshold so that, under independence or certain dependence, FDR is bounded by q.