Assess understanding of practical strategies for integrating qualitative and quantitative data in mixed-methods graduate research, including common design models (convergent, explanatory sequential, exploratory sequential), decisions about timing and priority, integration techniques (triangulation, data transformation, joint displays, meta-inference), sampling and validity implications, analytic pathways for merging or connecting datasets, and approaches to interpreting and reporting integrated findings, including handling discrepant results.