Applied Statistics Seminar on Tuesday (February 7, 2023) at 12 PM

Abstract: The exchangeability of units between treatment groups is a key and typically untestable assumption for evaluating causal intervention effects in observational studies. Standard methods assuming exchangeability can yield biased

Workshop on Research Methodology and Scientific Publication at ISRT for M.S. Students

Details can be found at https://www.isrt.ac.bd/workshop Date and Time: Sunday, 19th March 2023, 2:00 p.m. - 4:30 p.m. Venue: Institute of Statistical Research and Training (ISRT) , Room # 303 Technical Support: AdSEARCH by icddr,b Co-ordinators: Ahmed Ehsanur Rahman, Associate Scientist, MCHD, icddr,b Anisuddin Ahmed, Assistant Scientist and Project Coordinator, MCHD, icddr,b Session I: Experimental Study Designs

Seminar on Classification and Clustering for RNA-seq data with variable selection 

Speaker: Tanbin Rahman PhD, FDA, USA Title: Classification and Clustering for RNA-seq data with variable selection Abstract: Clustering and classification play an important role in identifying sub-types of complex diseases as well as building a predictive model in the field of medicine. In recent years, lowering of cost and high accuracy has made RNA-seq widely popular which

Applied Statistics Seminar on “Pairwise Accelerated Failure Time Models for Infectious Disease Transmission Within and Between Households”

isrt seminar room

Abstract: Pairwise survival analysis handles dependent happenings in infectious disease transmission data by analyzing failure times in ordered pairs of individuals. The contact interval in the pair ij is the time from the onset of infectiousness in i to infectious contact from i to j, where an infectious contact is sufficient to infect j if he

Seminar on “Data Science Product Development In the (AWS) Cloud” at 2 pm on July 24, 2023

Speaker: Sheikh Samsuzzhan Alam, Senior Data Science Developer for Operation, Novartis Pharma, Czech Republic Venue: ISRT seminar room Date and time: 2 pm on Monday, 24 July 2023 Title: Data Science Product Development In the (AWS) Cloud Abstract: Customer-facing software products are complex in nature and usually developed by multiple teams of engineers. On the other hand, software products