||Colorado State University
||1 credit hours - $590 per credit
||September 21, 2020 - October 23, 2020
This course will increase student understanding of best linear unbiased prediction and develop skills in genetic prediction. A wide array of material will be covered with emphasis on real-world datasets designed to develop applied analytical skills relative in animal breeding. Topics will include data integrity diagnosis, contemporary grouping strategies, adjusting for known non-genetic effects, the AWK Programming Language, UNIX/Linux scripting, and use of the Animal Breeder's Toolkit to perform genetic evaluations. Students will develop procedures for the utilization of various sources of information for the calculations of predictions of genetic merit in the form of estimated breeding values.
Prerequisite: Linear Models in Animal Breeding
R. Mark Enns
For course access questions, contact the teaching university’s campus coordinator. For enrollment questions, contact your home university campus coordinator.
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Disability Support Services
To request accommodations for this course, contact the disability support office at your home university. You must register each semester and for each course. Read more about the Great Plains IDEA process for requesting accommodations.
Approximately three weeks before the first day of class at Colorado State University, the CSU campus coordinator, Gayle Roslund
, emails course access instructions to students for courses taught by CSU. Using these instructions, students create their Colorado State eID (electronic identity). Students meeting all deadlines for eID creation and submission will have access to RamCT by the first day of class.
This course does not require an exam proctor.
This course does not include synchronous components.