Statistics is the science of data: measuring and assessing uncertainty and more generally, learning from data. Since scientific, technical, and social disciplines all need to make conclusions based on data, statistics provides them with tools essential for their advances. For example, in the 19th century, statistics was used to analyze patient mortality in military hospitals, leading to improved medical care. Today, promising new treatments are compared to current ones using experiments designed by following statistical principles.

Improvements in many industries require data analysis rather than guesswork. This extends even to sports. Once the performance of players and teams was judged mostly by eye. Nowadays more and more coaches and their staff use statistics to predict the most effective methods of game playing.

One of the many areas in which LLNL applies statistics is climate science. We use computer models based on physical laws to simulate the dynamics of the Earths atmosphere, land and oceans. The resulting data forms a basis for exploring the relationship among different components of the climate system and for making projections of future climate states. Despite their sophistication, climate models remain only approximations of a very complex system and their systematic errors together with many sources of uncertainty need to be quantified in order to estimate climate change impacts as well as to identify human effects on climate.

Speaker Bios

Dr. Ana Kupresanin

Dr. Kupresanin received her PhD in Mathematical Statistics from Arizona State University. She joined LLNL's Applied Statistics group in 2009 after spending several years as a faculty member teaching mathematics and statistics. having more than one thousand students attended her classes. Now, Dr. Kupresanin collaborates with engineers and scientists at LLNL to analyze data and develop statistical methodology for problems in diverse areas such as Stockpile stewardship (certification and uncertainty quantification), nuclear forensics, and climate modeling. She enjoys working with students and looks forward each year to the summer months when she hosts numerous summer interns.

Richard Newton

Richard Newton received his B.A. in Economics from the University of California at Davis and is the chairperson for the Mathematics Department at Tracy High School in Tracy, CA. With a wide range of teaching experience, including Algebra Readiness, Algebra 1, Geometry, Algebra 2, AP Statistics, and AP Computer Science A, Richard focuses on bringing technology into his classroom. He strives to make content more engaging by enriching it with real world context and challenges students by having them use and build computational models.

Richard has been a Master Teacher for Lawrence Livermore National Laboratory's Education Program since 2012. In 2015, he was awarded the Cortopassi Family Foundation Excellence in Mathematics Teaching Award. Richard is an instructor for the SIMMS (Secondary Integration of Modeling in Math and Science) Project with the intent of developing computer-modeling skills for high school science and math teachers within the San Joaquin County.