ST512 - Experimental Statistics for Biological Sciences II
- Prerequisites: ST511
- Term & Frequency: Fall, Spring, Summer II
- Student Audience: Graduate students in the life sciences. (Note that one section each Fall is restricted for Statistics graduate students.)
- Credit: 3 credits
- Recent Texts: Ott & Longnecker, An Introduction to Statistical Methods and Data Analysis. Statistical Research Methods in the Life Sciences
- Recent Instructors: Kevin Gross, Jason Osborne, Justin Post
- Background and Goals: ST512 is an applied course that introduces statistical methods
based on linear models for continuous response variables commonly used
in designed experiments. Examples include multiple linear regression,
factorial designs, and split-plot experiments. It is a prerequisite for
most advanced courses in statistics.
- Content: Simple and multiple regression. One- and two-factor ANOVA. Blocked and split-plot designs. A new section of ST 512 beginning Fall 2014 will add
a focus on categorical data analysis including regression with binary response Y (logistic regression) and analysis of data with multiple sources of error such as longitudinal data collected over time.
- Alternatives: ST514 provides analogous coverage for the social sciences. ST516 provides analogous coverage for engineers.
- Subsequent Courses: Many courses are available after taking ST 512, including ST 524, 708, 711, 721, 534, 537, 533.
S1 2017 Sections:
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