Bias Recognition and Analysis Validation Questions

Identifying, mitigating, and communicating biases and threats to validity across study design, data collection, analysis, and interpretation. Covers common bias types such as sampling bias, response bias, confirmation bias, question wording effects, and survivorship bias; approaches like triangulation, blind coding and inter rater reliability, robustness checks and sensitivity analyses, pre registration and replication where appropriate, and documenting limitations and alternative explanations. Emphasizes ethical considerations and building procedures to preserve analytical rigor.