|Statistics and Actuarial Science||Courses|
|Simon Fraser University||orcid 0000-0003-4568-1228|
Why Statistics? A core activity in science is collecting data to develop and evaluate theories about the way things work. To explore research questions, we design studies and then look at the resulting data to find meaning in the context of randomness. Statistics is the science of learning from data, and provides a principled framework and powerful set of methods to help with study design, modelling and analysis. I use statistics to understand inherited traits and patterns, while accounting for the way the data have been sampled, their randomness and dependencies. A central theme of my research is how DNA sequence variation reflects the many ways in which we are related. These relationships are often hidden and can tell us about our ancestry and origins. They have many uses including forensics (genetic genealogy), agricultural breeding, plant and wildlife conservation and genomic mapping in pursuit of disease treatments. Another research theme is integrating high-throughput and traditional clinical data to refine phenotypes and better discern patterns of disease inheritance. However, with big data come issues in statistical interpretation. For example: How do we design our research study to get the most information for our efforts? What are the sources of variation and of bias in our data? How do we tease apart the data patterns that are relevant from the ones that arise by chance, or through unrecognized biases in our sampling?
If you have interests in statistics and computing and share a curiousity about genetics and biology, please consider applying for graduate studies at SFU. I welcome collaborations with interested students and other scientists!
I am grateful to live, work and play on the unceded traditional territories of the Coast Salish peoples, including the səl̓ilw̓ətaʔɬ (Tsleil-Waututh), kʷikʷəƛ̓əm (Kwikwetlem), Sḵwx̱wú7mesh Úxwumixw (Squamish) and xʷməθkʷəy̓əm (Musqueam) Nations, on which SFU Burnaby is located. </p>