This chapter comprehensively details mixed methods research design and data analysis, highlighting its philosophical grounding in pragmatism integrating both quantitative and qualitative methods for a more complete understanding of complex phenomena. It underlines how mixed methods blend the “Art” of qualitative interpretation with the “Science” of quantitative rigor, a synergy now increasingly supported by AI tools for enhanced integration. The chapter then systematically introduces three primary mixed methods designs: Convergent Parallel, underlining simultaneous data collection and integration for mutual validation; Explanatory Sequential beginning with quantitative data to inform and explain qualitative findings; and Exploratory Sequential, starting with qualitative data to build and navigate subsequent quantitative phases. For each design, the text outlines data collection and analysis procedures, interpretation strategies, and critical validity considerations, offering practical examples from management research to demonstrate their application.