Observations from biological laboratory experiments, clinical trials, and health surveys always carry some amount of uncertainty. In many cases, especially for the laboratory experiments, it is inevitable to just ignore this uncertainty due to large variation in observations. Tools from statistics are very useful in analyzing this uncertainty and filtering noise from data. Also, due to advancement of microscopy and molecular tools, a rich data can be generated from experiments. To make sense of this data, we need to integrate this data a model using tools from statistics. In this course, we will discuss about different statistical tools required to
(i) analyze our observations,
(ii) design new experiments, and
(iii) integrate large number of observations in single unified model.
Intended Audience:BE Biotech/Biosciences/Bioengineering,MSc Biotech/Bio sciences/Bioengineering,
PhD Biotech/Biosciences/Bioengineering. It is taught as a core course for M. Tech Biomedical Engineering students at IIT Bombay.
Pre-requisites: Basic knowledge of 12th standard mathematics is sufficient.
Industries that will recognize this course:
Biotech companies, pharma companies and omics companies may be interested in this course.