May 18, 2017, 7:00 p.m.
Join us at Rutgers Open House and meet Professor Dobrzykowski and our students. Find out if Rutgers EMBA is right for you!
Price
FREE
Rutgers Open House – May 2017
Rutgers Open House – May 2017
- Start07:00 PM - May 18 2017
- End09:00 PM - May 18 2017
- 1 Keong Saik Rd, Singapore 089109
- +65 6805 4007
- info@rutgers.edu.sg
Business Statistics
By Professor David Dobrzykowski
About the Professor:
Dr. David Dobrzykowski is a tenured Associate Professor in the Department of Supply Chain Management in Rutgers Business School (RBS) – Newark and New Brunswick where he teaches graduate courses in Healthcare Services Management, Operations Analysis, Project Management, and Business Statistics. He is also Director of the Masters of Science in Healthcare Services Management program. Dr. Dobrzykowski’s research identifies best practices for information processing and supply chain coordination with a specific interest in healthcare delivery. He has over 20 research publications in Journal of Supply Chain Management, Journal of Operations Management, Decision Sciences, and other outlets, and he has recently co-authored a book titled “Healthcare Solutions: A Patient-Centered, Resource Management Perspective,” available from CRC Press / Taylor & Francis.
Prior to his doctoral studies, Dr. Dobrzykowski served in a variety of management roles in the healthcare sector with organizations such as Catholic Health Partners and UnitedHealthcare. As an academic, he has worked with a variety of industry partners including Henry Ford Health System, Barnabus Health System, McLaren Health System, Sisters of St. Francis Continuing Care Retirement Community (CCRC), Wesleyan Senior Living CCRC, Seneca Medical, and the healthcare vertical of UPS. He has taught executive education sessions for leaders from top companies like UPS, Novartis, Schindler, Verizon, Panasonic, PSEG, Becton Dickinson, Johnson & Johnson, Pfizer, Bayer, S&P, and Sony.
About the Subject
Business Statistics introduces the use of statistical methods and probability in the analysis and modeling of business problems. Cutting-edge software applications coupled with a strong focus on the interpretation of computational results, yield powerful applicability to real-world decision-making. Examples are drawn from such settings as supply chain management, pharmaceuticals, health care, market research, quality control, and production.
