Brett Saraniti received his PhD in Managerial Economics and Decision Sciences from the Kellogg School of Management at Northwestern University in 1997. His dissertation chair was Roger Myerson, Nobel Laureate 2007. He is currently a Clinical Professor of Managerial Economics and Decision Sciences at Kellogg.
Brett has taught MBA and executive courses at Kellogg every summer since 1995 where he has been honored with four teaching awards for three different courses. He has also taught in the Kellogg-Recanati program in Tel Aviv, the Kellogg-Schulich program in Toronto, The Kellogg-Guanghua program in Beijing, and the Kellogg-HKUST program in Hong Kong. Brett was a visiting professor at INSEAD every year from 2008-17 winning the Best Teacher Award for the Core Classes in September 2008. He has been a visitor at the Sasin Graduate Institute in Bangkok, Thailand; IESE in Barcelona; the Brisbane Graduate School of Business in Queensland, Australia; the Thunderbird School of Global Management; TECNUN in San Sebastian, Spain; The Bloch School at UMKC; Stanford; UC Davis; and the Helsinki School of Economics and Business Administration in Finland. He has also delivered executive management seminars at Seminarium International in both Chile & Costa Rica and Seminarium Mexico.
He has also worked, taught, and/or consulted for McKinsey & Company, Xerox Corporation, Hiscox Insurance, Allianz, Chevron Oil Field Research, LG Electronics, Cantor Fitzgerald/Hollywood Stock Exchange, Alstom, Swire, FEMSA, EVRAZ N.A., HP, UNext, Love & Kirschenbaum LLC (expert witness), Maclean-Fogg, Trunk Club, MRJ Technologies, Suncloud Health, Chipin.com, Carddomains.com, Lee Ceramics, and Surflight Hawaii. He is on the corporate advisory board of Sprint Milestone, a data analytics consultancy based in Hong Kong.
Brett spends most of his time with his wife Samantha and their three children Francesca, Carlo & Enzo who enjoy beating him at pretty much everything.
This sequel to DECS-430 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables, primarily through multivariate regression. In addition to learning basic regression skills, including modeling and estimation, students will deepen their understanding of hypothesis testing and how to make inferences and predictions from data. Students will also learn new principles such as identification and robustness. The course has an intense focus on managerial relevant applications, cases and interpretations.