Building 3, Level 4. Office number: 4326-WS15
Analytical Statistician/ data scientist with extensive experience of applied and methodological research in academia. Enthusiastic for data analysis and interested in the applying statistical methods and analytical techniques for real life data. My current research focuses on developing statistically robust analysis to understand and finding patterns in samples from different conditions or environments in metagenomic datasets derived from the KAUST Metagenomic Analysis Platform (KMAP).
No evidence for temperature-dependence of the covid-19 epidemic. T. Jamil, I. Alam, T. Gojobori & C. M. Duarte. Frontiers in Public Health, 8, 436. (2020).https://doi.org/10.3389/fpubh.2020.00436
Multiple stressor eﬀects on coral reef ecosystems. J. I. Ellis, T. Jamil, H. Anlauf, ... , I. Hoteit. Global Change Biology, 25(12), 4131–4146. (2019).https://doi.org/10.1111/gcb.14819
Marine heatwaves reveal coral reef zones susceptible to bleaching in the red sea. L. G. C. Genevier, T. Jamil, D. E. Raitsos, G. Krokos, & I. Hoteit. Global Change Biology, 25(7), 2338–2351. (2019).https://doi.org/10.1111/gcb.14652
Default “Gunel and Dickey” Bayes factors for contingency tables.T. Jamil, A. Ly, R. D. Morey, J. Love, M. Marsman & , E.-J. Wagenmakers. Behavior research methods, 49(2), 638–652. (2017).https://doi.org/10.3758/s13428-016-0739-8
What are the odds? Modern relevance and Bayes factor solutions for MacAlister’s problem from the 1881 Educational Times. T. Jamil, M. Marsman , A. Ly, R. D. Morey &E.-J. Wagenmakers. Educational and Psychological Measurement, 77(5), 819–830. (2017).https://doi.org/10.1177/0013164416667980
Bayesian inference for psychology. Part I: Theoretical advantages and practical ramiﬁcations. E.-J. Wagenmakers. M. Marsman, T. Jamil, A. Ly, J. Verhagen, J. Love, et al. Psychonomic bulletin & review, 25(1), 35–57. (2018).https://doi.org/10.3758/s13423-017-1343-3