Test A/B ngir quiz model ML

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan moo waral ekip A/B yi di natt ay model ci liggéey bi, duñu wóolu metrics yi nekk ci biti?
   • Benn model bu am njubte bu gëna baax ci offline mën na gaañ metrics liggéey dëgg
   • jagleel yi nekkul ci net bi jagul yoon
   • Defar moo gëna xéewale test bi nekk ci biti
   • Done yi nekkul ci net bi amul
2. Ban cër la devoir aleatoire di def ci examen A/B?
   • Dafay tax test bi gëna gaaw
   • It supports balance between groups in expectation, subject to design and implementation assumptions
   • Dafay efaase jëfandikukat yi
   • Dafay wàññi limu model yiñ soxla
3. In a model A/B test, what usually happens in the treatment group?
   • The candidate scores requests but all outputs are withheld
   • Every user is assigned to both models for the same decision
   • The candidate model serves user-facing decisions for the randomly assigned group
   • The control model is removed before any comparison
4. Under a null hypothesis and stated test assumptions, how is a p-value interpreted?
   • As the probability that the null hypothesis is true
   • As the probability that the treatment caused the observed result
   • As the probability that the experiment will replicate
   • As the probability of data at least this extreme if the null hypothesis holds
5. How can a multi-armed bandit change an experiment while it runs?
   • It can allocate more traffic to variants with better observed outcomes and less to others
   • It keeps every variant at a fixed equal allocation throughout
   • It removes randomization from every assignment
   • It guarantees the best variant is identified without uncertainty
6. Luy njariñu jàngat doole balaa test A/B?
   • Tann logo ngir jàngat bi
   • Xayma ñaata jëfandikukat lañu soxla ngir mëna gis effet dëgg
   • Ngir enkripte dem bi ak dikk bi
   • Ngir efaase kuréel giy saytu
7. What does a sample-ratio mismatch (SRM) signal during an A/B test?
   • The treatment model is necessarily better
   • The experiment has sufficient statistical power
   • Observed assignment counts differ materially from the configured allocation, which can indicate a data or randomization problem
   • The primary metric improved causally
8. Why include guardrail metrics alongside an experiment’s primary success metric?
   • To guarantee the candidate wins on every metric
   • To replace the primary metric after results are observed
   • To avoid defining a decision rule before the test
   • To detect meaningful harms in other outcomes even when the primary metric improves