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20.260/20.560
Analysis and Presentation of Complex Biological Data Paul Blainey Mon, Wed, Fri, Jan 14, 16, 18, 21, 23, 25, 28, 30, 1, 01-04:00pm, 16-220 Pre-register on WebSIS and attend first class. Limited to 25 participants. No listeners Prereq: Permission of instructor Level: U 4 units Graded P/D/F Illustrates best practices in the statistical analysis of complex biological datasets and the graphical representation of such analyses. Covers fundamental concepts in probability and statistical theory as well as principles of information design. Provides mathematical concepts and tools that enable students to make sound judgments about the application of statistical methods and to present statistical results in clear and compelling visual formats. Assignments focus on key concepts and their application to practical examples. Assumes basic knowledge of calculus and programming in MATLAB or R. Students taking graduate version complete additional assignments. January 21, - MLK Holiday - Optional Session with enrichment material Contact: Paul Blainey, Broad, x4-7320, pblainey@mit.edu |
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20.300
Advanced Workshop in Biological Engineering Communication: Professors Share Their Practices BE Communication WKSHP E. Alm, Agnieszka (Agi) Stachowiak Wed Jan 23, Fri Jan 25, Mon Jan 28, Wed Jan 30, Fri Feb 1, 10am-04:00pm, 56-614, MWF 10-12, 1-4 Pre-register on WebSIS and attend first class. Limited to 25 participants. No listeners Prereq: Permission of instructor Level: U 3 units Graded P/D/F Working scientists and engineers discuss best practices for written, visual, and oral communication in the classroom, the lab, and the workplace. In a series of lectures, successful academics and industry professionals share how they prepare papers, talks, and graphics. Recitations allow deeper exploration of the lecture topics. With faculty guidance, students develop their own projects during workshops. Emphasizes systematic approaches and transferable skills such as effective drafting and revision. Topics include creating compelling visuals to represent data and concepts; formal/informal writing, from research papers to cover letters; and developing memorable talks and presentations. Examples drawn from biological engineering research. Enrollment limited; preference to Course 20 majors. Contact: Agi Stachowiak, 16-319, x4-1940, astachow@mit.edu |
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20.560/20.260
Analysis and Presentation of Complex Biological Data Paul Blainey Mon, Wed, Fri, Jan 14, 16, 18, 21, 23, 25, 28, 30, 1, 01-04:00pm, 16-220 Pre-register on WebSIS and attend first class. Limited to 25 participants. No listeners Prereq: Permission of instructor Level: G 4 units Graded P/D/F Illustrates best practices in the statistical analysis of complex biological datasets and the graphical representation of such analyses. Covers fundamental concepts in probability and statistical theory as well as principles of information design. Provides mathematical concepts and tools that enable students to make sound judgments about the application of statistical methods and to present statistical results in clear and compelling visual formats. Assignments focus on key concepts and their application to practical examples. Assumes basic knowledge of calculus and programming in MATLAB or R. Students taking graduate version complete additional assignments. January 21 - MLK Holiday - Optional Session with enrichment material Contact: Paul Blainey, Broad, (617) 714-7320, pblainey@mit.edu |