Quantcast

'STATS COURSE - Advancing in R - last few places stlll available'

classic Classic list List threaded Threaded
1 message Options
Threaded
Open this post in threaded view
|  
Report Content as Inappropriate

'STATS COURSE - Advancing in R - last few places stlll available'

Oliver Hooker
"Advancing in Statistical Modelling using R"

Delivered by Dr. Luc Bussiere and Dr. Tom Houslay

http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/

This course will run from 5th – 9th December 2016 at Juniper Hall
Field Station, Dorking, Surrey, just south of London, England

This is an introduction to model selection and simplification,
generalised linear models, mixed effects models and non-linear models.

The course is aimed at biologists with a basic to moderate knowledge in
R. The course content is designed to bridge the gap between basic R
coding and more advanced statistical modelling. This five day course
will consist of series of modules, each lasting roughly half a day and
comprised of lectures and practicals designed to either build required
skills for future modules or to perform a family of analyses that is
frequently encountered in the biological literature.

Course content is as follows
Day 1 Course introduction
• Techniques for data manipulation, aggregation, and visualisation;
introduction to linear regression. Packages: {tidyr}, {dplyr}, {ggplot2}
Day 2 Linear models
• Diagnostics, collinearity, scaling, plotting fitted values); fitting
and interpreting interaction terms; model selection and simplification;
general linear models and ANCOVA.
• Packages: {stats}, {car}
Day 3 Generalized linear models
• Logistic and Poisson regression; predicting using model objects and
visualizing model fits.
• Packages: {broom}, {visreg}, {ggplot2}
Day 4 Mixed effects models
• Theory and practice of mixed effect models; visualising fixed and
random effects.
• Packages: {lme4}, {broom}, {ggplot2}, {sjPlot}
Day 5 Fitting nonlinear functions
• Polynomial & Mechanistic models; brief introduction to more advanced
topics & combining methods (e.g., generalised linear mixed effects,
nonlinear mixed effects, and zero-inflated and zero-altered models).
• Packages: {nlsTools}.
• Afternoon to discuss own data if time permits

Please email any inquiries to [hidden email] or visit our
website www.prstatistics.com

Please feel free to distribute this material anywhere you feel is
suitable

Our other courses- email [hidden email] for details

1. ADVANCING IN STATISTICAL MODELLING USING R (December 2016, April
2017, December 2017
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/
2. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (November 2016, July
2017)
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae04/
3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017)
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/
4. GENETIC DATA ANALYSIS USING R (TBC)
5. BIOINFORMAITCS FOR GENETICISTS AND BIOLOGISTS (July 2017)
6. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017)
7. INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS (April 2017)
8. INTRODUCTION TO PYTHON FOR BIOLOGISTS (TBC)
9. TIME SERIES MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS (TBC)
10. ADVANCES IN MULTIVAIRAITE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017)
11. ADVANCES IN DNA TAXONOMY (TBC)
12. INTRODUCTION TO BIOINFORMATICS USING LINUX (TBC)
13. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/
14. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (TBC)
15. PHYLOGENETIC DATA ANALYSIS USING R (TBC)
16. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
(January 2017)
17. ADVANCED PYTHON FOR BIOLOGISTS (February 2017)
18. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March)
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/
19. GEOMETRIC MORPHOMETRICS USING R (June)
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
20. INTRODUCTION TO METHODS FOR REMOTE SENSING (TBC)
21. ECOLOGICAL NICHE MODELLING (TBC)
22. ANIMAL MOVEMENT ECOLOGY (TBC)


Oliver Hooker PhD.

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/Oliver Hooker

PR statistics
3/1
128 Brunswick Street
Glasgow
G1 1TF
+44 (0) 7966500340

_______________________________________________
R-sig-ecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Loading...