Introduces fundamental data due diligence, reliability, data correction, and recoding processes and practices as they apply to the insurance industry. Expands on approaches to discerning and validating patterns in data through sound applications of the scientific method. Emphasizes regression, chi-square and ANOVA testing, regularization, and generalized linear models. Offers students an opportunity to obtain the fundamental data management, review, reengineering, and exploration skills required to successfully develop the data analytical competencies in demand across the insurance industry.