Model Unique Recipients with Poisson Distribution and Test Fit
MetaData Scientist · Technical Screen
Last updated
Evaluates statistical modeling of unique recipient counts per caller using count distributions. Strong answers compare Poisson, binomial, negative binomial, zero-inflated, and segmented models, then test fit with dispersion checks, likelihood metrics, chi-square tests, and simulation-based diagnostics.
Scenario
Modelling the distribution of the number of unique recipients each caller contacts to support capacity and growth planning.
Question
Which statistical distribution would you use to model the number of recipients per caller and how would you test the goodness-of-fit?
Hints
Compare Poisson, binomial, negative-binomial; check over-dispersion; fit via maximum likelihood; validate with chi-square, KS test, or AIC.
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