This is intended to provide students interested in biomedical research with an introduction to core statistical concepts and methods, including experimental design. The course also provides a good foundation in the use of discovery tools provided by a data analysis and visualization software. The topics covered will include: i) Importance of being uncertain; ii) Error bars; iii) Significance, p-values and t-tests; iv) Power and sample size; v) Visualizing samples with box plots; vi) Comparing samples; vii) Non parametric tests; viii) Designing comparative experiments; ix) Analysis of variance and blocking; x) Replication; xi) Two-factor designs; xii) Association, correlation and causation; xiii) Simple linear regression; xiv) Regression diagnostics. The concepts will be illustrated with realistic examples that are commonly encountered by biomedical researchers (as opposed to the simpler examples described in entry-level textbooks). The statistical softwares used in this course are JMP and R Studio.