Sample interview questions: How do you handle situations where there are limitations in the availability of historical data?
Sample answer:
Data Augmentation Techniques:
- Synthetic Data Generation: Create artificial datasets that exhibit similar statistical properties to the original data.
- Data Imputation: Fill in missing values using statistical techniques such as regression models or k-nearest neighbors.
- Bootstrapping: Resample the available data with replacement to generate multiple datasets, increasing the effective sample size.
Alternative Data Sources:
- Proxy Data: Utilize correlated data that may provide insights into the missing historical data.
- Domain Knowledge: Leverage expert opinions or industry reports to extrapolate missing data.
Modeling Techniques:
- Bayesian Inference: Incorporate prior beliefs or assumptions to make inferences with limited data.
- Robust Estimation: Use estimators that are insensitive to outliers and missing observations.
- Ensemble Methods: Combine multiple models trained on different subsets of the data to reduce bias and improve accuracy.
Scenario Analysis:
- Sensitivity Analysis: Assess the impact of variations in the missing data on model outcomes.
- Extreme Value Theory: Consider extreme scena… Read full answer
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