Model Rare Events with a Log Link and Handle Zero Counts
Company: Waymo
Role: Data Scientist
Category: Statistics & Math
Difficulty: medium
Interview Round: Technical Screen
# Model Rare Events with a Log Link and Handle Zero Counts
Explain how a log-form model can be used for rare-event data and why it may be useful. Be precise about whether you are transforming observed outcomes or modeling a mean or rate. Explain how zero observed events are handled, and state the assumptions needed for your proposed model.
### What a Strong Answer Covers
- A defined outcome and exposure, with a log link for a positive mean or rate.
- The difference between a log-linked count model and taking the logarithm of the observed count.
- Treatment of zeros without an arbitrary unsupported replacement.
- Overdispersion, dependence, and distinctions between binary and count outcomes.
```hint Locate the logarithm
A zero observation does not imply that the model must take log zero.
```
### Follow-up Questions
- What changes if the data have more zero counts than a Poisson model predicts?
- How do you compare units observed for different amounts of exposure?
Overview: Explain rare-event log-link models, exposure offsets, zero counts, overdispersion, and the difference between counts and binary outcomes.
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