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Explain P-Value Reporting and Bootstrap for Coefficient Estimation

VoleonData Scientist · Technical Screen
MediumData ScientistTechnical ScreenStatistics & Math

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This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Explain P-Value Reporting and Bootstrap for Coefficient Estimation states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Scenario

Voleon DS tech round: statistical inference checks after regression.

Question

You observe a p-value printed as 0.000 for a coefficient. Is this possible? Why might software report it that way, and how do you communicate significance appropriately?

Follow-up: Explain how you would use bootstrapping to estimate the sampling distribution of this coefficient and relate the bootstrap expectation to the true population parameter.

Hints

Discuss numerical rounding, significance thresholds, reporting scientific notation, bootstrap resampling, bias and variance.