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Explores the distinction between association and causation in statistical analysis, highlighting the limitations of association in inferring causation.
Explores the significance of randomization in protein mass spectrometry and proteomics, highlighting its role in minimizing bias and ensuring research validity.
Explores the challenges of inferring epidemiological parameters from clinical data, focusing on COVID-19 and the complexities of estimating infection fatality ratios.
Explores the consistency and asymptotic properties of the Maximum Likelihood Estimator, including challenges in proving its consistency and constructing MLE-like estimators.
