Statistical literacy for deep tech
by Noel Jee
Understanding how to effectively discuss and interpret statistics and scientific data is incredibly important for both investors and founders. This seminar was meant to arm investors with basic statistical literacy when deciding to partner with a company during due diligence. It was also meant to help founders understand how investors assess statistics and scientific data. Increasing literacy and comfort with scientific terminology among the broader community enables investors to better communicate with and support these founders.
Using life science case studies, this seminar communicated in clear terms some of the most important measurements and tests applied by deep tech start-ups, such as: sensitivity vs specificity, false positive vs negative rate, prospective vs retrospective studies, multiple hypothesis corrections, regression and other basic statistical models (p-value, t-test, etc).
This seminar was produced and presented by Noel Jee, a Principal at Illumina Ventures, who focuses on therapeutics and diagnostics. Prior to joining the fund, Noel worked at L.E.K. Consulting as a management consultant specializing in life sciences. He has consulted on strategy engagements for companies in the pharmaceuticals, biotech, and diagnostics industries. He obtained a dual B.S. degree from the University of Maryland College Park, and a PhD in Chemistry and Chemical Biology from the University of California San Francisco.
You can watch this event on YouTube here.
