# Christine Baes: Catalogue data in Spring Semester 2015

Name | Dr. Christine Baes |

Address | Lehre Umweltsystemwissenschaften ETH Zürich, TAN F 1 Tannenstrasse 1 8092 Zürich SWITZERLAND |

Telephone | +41 44 632 33 49 |

Department | Environmental Systems Science |

Relationship | Lecturer |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

751-6212-00L | Genetic Evaluation of Lifestock | 1 credit | 1G | C. Baes | |

Abstract | Methods for practical genetic evaluation in livestock populations are presentend and applied in assignments using small numerical examples. Applications in practical pig and cattle breeding are dealt with in guest lectures. | ||||

Objective | The students know the most important methods used for genetic evaulation in livestock populations. They are able to apply these methods to simple examples. | ||||

Content | - Selection index and BLUP - The BLUP Multitrait Animal Model - Genetic evaulation using maternal effekts - Random Regression and the test day model - Guest lectures on practical applications of genetic evaluation in pigs and cattle. | ||||

Lecture notes | Copies of the slides are available on the net. | ||||

Literature | To be announced in the lectures. | ||||

751-7602-00L | Applied Statistical Methods in Animal Science | 1 credit | 2V | C. Baes | |

Abstract | Refresh matrix operations and solving of systems of linear equations using the generalised inverse. Introduction to theory and application of linear models: regression, models with fixed effects (one factor, multiple factors, interactions), models with random effects, mixed models. Assignments using the statistics programmes R and SAS. | ||||

Objective | The students are familiar with matrix operations and the solving of systems of linear equations. They know the possibilities to solve systems of linearly dependent equations using the generalized inverse. They are able to set up linear models for the analysis of animal science data. They know the difference between fixed and random effects. They are familiar with the application of the statistics programmes R and SAS to solve linear models and to interpret their results. | ||||

Content | - Matrix algebra, systems of linear equations, generalised inverse - Linear models with fixed effects: - Regression: simple linear, multiple, non linear regression - Models with 1 factor, 2 factors (without and with interaction), generalisation - Linear models with random effects, mixed linear models | ||||

Lecture notes | Copies of the slides are available on the net. | ||||

Literature | To be announced in the lectures. |