General information
Programa do Curso (30 horas)
Session 1. 6 October 9:00 – 17:00 h
1.1 Basics of R language I. 9:00 – 9:50 h
1.2 Basics of R language II. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Basics or R language III. 11:10 – 12:00 h
1.4 Basics of R language IV. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Basics of R language V. 15:00 – 15:50 h
1.6 Basics of R language VI. 16:00 – 16:50 h
Session 2. 7 October 9:00 – 17:00 h
1.1 Linear Regression. 9:00 – 9:50 h
1.2 Non linear Regression. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Non parametric Regression. 11:10 – 12:00 h
1.4 General Linear Model I. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 General Linear Model II: Hierarchical designs. 15:00 – 15:50 h
1.6 General Linear Model III: Mixed effects designs. 16:00 – 16:50 h
Session 3. 8 October 9:00 – 17:00 h
1.1 General Linear Model IV: Mixed effects designs with random slopes. 9:00 – 9:50 h
1.2 Generalized Linear Model I. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Generalized Linear Model II. 11:10 – 12:00 h
1.4 Generalized Additive Models I. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Generalized Additive Models II. 15:00 – 15:50 h
1.6 Meta – Analysis I. 16:00 – 16:50 h
Session 4. 9 October 9:00 – 17:00 h
1.1 Meta – Analysis II 9:00 – 9:50 h
1.2 Multivariate statistics I: Extensions of univariate tests. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Multivariate statistics II: Ordination methods. 11:10 – 12:00 h
1.4 Multivariate statistics III: Ordination methods. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Multivariate statistics IV: Classification methods. 15:00 – 15:50 h
1.6 Multivariate statistics V: Classification methods. 16:00 – 16:50 h
Session 5. 10 October 9:00 – 17:00 h
1.1 Building dynamic models in R I. 9:00 – 9:50 h
1.2 Building dynamic models in R II. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Optimizing models I. 11:10 – 12:00 h
1.4 Optimizing models II.12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Analyzing model behavior I. 15:00 – 15:50 h
1.6 Analyzing model behavior II. 16:00 – 16:50 h
Sobre o Profesor
Aldo Barreiro é licenciado en Bioloxía pola Universidade de Vigo (2001) e doutor no departamento de ecoloxía da mesma universidade (2007). Realizou estancias post-doutorais na Universidade de Cornell (Ithaca, USA) entre 2008-2010 e desde 2011 é investigador post-doutoral no CIIMAR (Oporo, Portugal). O seu campo de investigación xirou o en torno a varios aspectos da ecoloxía do plancton. É coautor dos libros de estatística "Tratamiento de Datos" (2006) e "Tratamiento de Datos con SPSS Statistica y R" (2011), da editorial Díaz de Santos. Ten impartido varias edicións dun curso de R aplicado a estadística para investigación no CIIMAR.
Content
The highlighted icons, represent the fields of education (in compliance with ISCED Classification) engaged during this course/programme.
Venue
Vigo, Spain
ECIMAT Marine Station
Illa de Toralla, E-36331 Coruxo, Vigo, Galicia
Application
Click here to apply: http://www.ecimat.org/index.php?option=com_rsform&formId=8
Cost:
<p>100€</p>
Prerequisites:
Hai 20 prazas disponibles para participar no curso, darase prioridade aos investigadores pertencentes a grupos de investigación da Agrupación Océano-Ecimat.
Application Procedure:
Para inscribirse pulsar aquí. A realización do curso estará supeditada a acadar un número mínimo de inscritos.
A data de peche de inscripcións é: 26/09/2014
Grant Opportunities:
Os investigadores adscritos a Grupos de Investigación da Agrupación Océano-Ecimat poden solicitar o financiamento do 100% do custe de inscripción.
Qualification
Programa do Curso (30 horas)
Session 1. 6 October 9:00 – 17:00 h
1.1 Basics of R language I. 9:00 – 9:50 h
1.2 Basics of R language II. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Basics or R language III. 11:10 – 12:00 h
1.4 Basics of R language IV. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Basics of R language V. 15:00 – 15:50 h
1.6 Basics of R language VI. 16:00 – 16:50 h
Session 2. 7 October 9:00 – 17:00 h
1.1 Linear Regression. 9:00 – 9:50 h
1.2 Non linear Regression. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Non parametric Regression. 11:10 – 12:00 h
1.4 General Linear Model I. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 General Linear Model II: Hierarchical designs. 15:00 – 15:50 h
1.6 General Linear Model III: Mixed effects designs. 16:00 – 16:50 h
Session 3. 8 October 9:00 – 17:00 h
1.1 General Linear Model IV: Mixed effects designs with random slopes. 9:00 – 9:50 h
1.2 Generalized Linear Model I. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Generalized Linear Model II. 11:10 – 12:00 h
1.4 Generalized Additive Models I. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Generalized Additive Models II. 15:00 – 15:50 h
1.6 Meta – Analysis I. 16:00 – 16:50 h
Session 4. 9 October 9:00 – 17:00 h
1.1 Meta – Analysis II 9:00 – 9:50 h
1.2 Multivariate statistics I: Extensions of univariate tests. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Multivariate statistics II: Ordination methods. 11:10 – 12:00 h
1.4 Multivariate statistics III: Ordination methods. 12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Multivariate statistics IV: Classification methods. 15:00 – 15:50 h
1.6 Multivariate statistics V: Classification methods. 16:00 – 16:50 h
Session 5. 10 October 9:00 – 17:00 h
1.1 Building dynamic models in R I. 9:00 – 9:50 h
1.2 Building dynamic models in R II. 10:00 – 10:50 h
Coffee break 10:50 – 11:10 h
1.3 Optimizing models I. 11:10 – 12:00 h
1.4 Optimizing models II.12:10 – 13:00 h
Lunch break 13:00 – 15:00 h
1.5 Analyzing model behavior I. 15:00 – 15:50 h
1.6 Analyzing model behavior II. 16:00 – 16:50 h
Sobre o Profesor
Aldo Barreiro é licenciado en Bioloxía pola Universidade de Vigo (2001) e doutor no departamento de ecoloxía da mesma universidade (2007). Realizou estancias post-doutorais na Universidade de Cornell (Ithaca, USA) entre 2008-2010 e desde 2011 é investigador post-doutoral no CIIMAR (Oporo, Portugal). O seu campo de investigación xirou o en torno a varios aspectos da ecoloxía do plancton. É coautor dos libros de estatística "Tratamiento de Datos" (2006) e "Tratamiento de Datos con SPSS Statistica y R" (2011), da editorial Díaz de Santos. Ten impartido varias edicións dun curso de R aplicado a estadística para investigación no CIIMAR.
Para inscribirse pulsar aquí. A realización do curso estará supeditada a acadar un número mínimo de inscritos.
A data de peche de inscripcións é: 26/09/2014
Hai 20 prazas disponibles para participar no curso, darase prioridade aos investigadores pertencentes a grupos de investigación da Agrupación Océano-Ecimat.
