Lecture, four hours. Requisite: at least one course in probability or statistics that included basic probability, elementary distributions, hypothesis testing, and confidence intervals; knowledge of elementary calculus. Familiarity with elementary matrix algebra and previous programming experience are strongly preferred. Modern scientific research and quality and quantity of data have been greatly affected by rapid expansion of statistical computing software. Problem-oriented study of latest methods in applied statistical data analysis and its use arising in laboratory and clinical research. S/U or letter grading.

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Course

Instructor
Jeffrey A. Gornbein
Previously taught
24S 23S 22S 21S 20S 19S

Previous Grades

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