'STATS COURSE - Advancing in R'

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'

Oliver Hooker
"Advancing in Statistical Modelling using R"

Delivered by Dr. Luc Bussiere and Dr. Tom Houslay

http://prstatistics.com/course/advancing-in-statistical-modelling-using-r-ad

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, mixed
effects models, generalised linear 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

Upcoming courses - email for details [hidden email]
1. GENETIC DATA ANALYSIS USING R (August)
2. INTRODUCTION TO BIOINFORMATICS USING LINUX (August)
3. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August)
4. INTRODUCTION TO PYTHON FOR BIOLOGISTS (October)
5. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October)
6. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(October)
7. PHYLOGENETIC DATA ANALYSIS USING R (October/November)
8. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (November)
9. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
(January)
10. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March)
11. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June)

Dates still to be confirmed - email for details
[hidden email]
• STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
• INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS
• BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS

Oliver Hooker
PR statistics
3/1
128 Brunswick Street
Glasgow
G1 1TF
+44 (0) 7966500340
www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/Oliver Hooker

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