The objective of biomedical data analysis is to discover useful and meaningful patterns hidden in the biomedical data. Statistical tools (measurements and tests) are often necessary to assess the “usefulness” and “meaningfulness” of patterns. In the literature, the commonly used statistical tools include t-test, Chi-2 test, fisher’s exact test, etc. All the statistical tools are developed and can be applied under certain assumptions and constrains. However, many researchers tend to apply the statistical tools without careful examination of the validness of the underlying assumption. This may often lead to false discoveries and invalid conclusions. A researcher needs to know the commonly used statistical tools for biomedical data analysis along with their underlying assumptions and constraints.
Sign up for our 25 May symposium to avoid common mistakes in applying these tools, and learn about alternatives and necessary corrections!
Speaker Biography
Dr. Feng Mengling is currently working as a Scientist in the Data Mining Department of Institute for Infocomm Research (I2R), A*STAR. He is involved in a wide spectrum of research projects across the fields of bio-imaging, bioinformatics, medical data analysis, continuous time-series analysis, data mining for business strategies and fundamental data mining. Dr. Feng has found his real interest in knowledge discovery and data analysis during his PhD study with Prof. Wong Limsoon and Prof. Tan Yap-Peng. Dr. Feng’s current research focus is on biostatistics, data mining for business intelligence and medical time-series analysis.
