I teach Statistics, Data Analysis, and Data Mining courses at the Smith School. The two main courses that I've been teaching are Data Mining for Business (MBA) and Scientific Data-Collection (PhD).

I have been teaching, designing, and updating courses in statistics and data mining since 1994. I've taught engineers, statisticians, social science students, and now business students (undergrad, MBA, and PhD). My teaching career kicked off as a teaching assistant during my B.A. and M.Sc. studies. During my Ph.D. studies at the Israel Institute of Technology, I became instructor for “Industrial Statistics”. At Carnegie Mellon University I taught “Engineering Statistics and Quality Control” and “Sampling, Surveys, and Society”.

My teaching philosophy is based on my own teaching experience as well as on dialogues with leading teachers and textbook writers, and on recent papers, websites, textbooks, and conferences. I value interactive and hands-on learning, and take advantage of "good" technology (great software, clickers, Blackboard, blogs, etc.) My principles of teaching are:

• Demonstrate the value of what you teach
• Emphasize conceptual understanding instead of formulas
• Use real data and real problems
• Foster experimental and active learning instead of memorization
• Have students work in teams
• Provide immediate feedback