Ron S. Kenett, University of Turin
This talk is a journey meandering between science and business analytics. To provide context I will first list, very briefly, my role models. Specifically, I will mention Sir David Cox, who taught me the introduction to statistics class as an undergraduate at Imperial College; Sam Karlin, who was my PhD adviser at Stanford and the Weizmann Institute; George Box and Bill Hunter, who opened the door for me to applied statistics in business and industry; as well as Stu Hunter, Ed Deming and Joe Juran. They all had a significant impact on my career. The next stop on the journey will provide a brief introduction to Quality by Design (QbD), as applied in the pharmaceutical industry. The third stop will discuss a topic of growing concern in science – reproducibility of research findings. To address this issue, I will sketch a new proposal based on generalizability of findings. Generalization is one of the eight dimensions of information quality (InfoQ), and this stop represents joint work with Galit Shmueli carried over the last eight years and summarized in our recent book. A final stop will discuss challenges ahead for analytics and statistics. The motivation behind this journey is to demonstrate the key role of statistical thinking in modern analytics and its impact both on science and business applications. Eventually, these thoughts and examples are driven by the ambition to put statistics back in the driver’s seat of data-driven work. Throughout, I will show some examples using JMP to make the case.