STATS COURSE - Advancing in statistical modelling using R

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STATS COURSE - Advancing in statistical modelling using R

Oliver Hooker
"Advancing in Statistical Modelling using R"

Delivered by Dr. Luc Bussiere and Dr. Ane Timenes Laugen

http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/

This course will run from 24th - 28th April 2017 at Margam Park
Discovery Centre, Wales.

Course only and all inclusive packages are available.

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
1. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/

2. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017) #SIMM
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/

3. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/

4. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017) #MVSP
http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/

5. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/

6. CODING, DATA MANAGEMENT AND SHINY APPLICATIONS USING RSTUDIO FOR
EVOLUTIONARY BIOLOGISTS AND ECOLOGISTS (May 2017) #CDSR

7. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/

8. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/

9. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)

10. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/

11. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

12. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

13. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL
http://www.prstatistics.com/course/introduction-to-bioinformatics-using-linux-ibul02/

14. GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR

15. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY
BIOLOGISTS (October 2017) #SEMR

16. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017
TBC) #LNDG
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg02/

17. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017) #ABME
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

18. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS

19. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB
http://www.prstatistics.com/course/introduction-to-python-for-biologists-ipyb04/

20. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017)
#DVMP
http://www.prstatistics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/

21. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr07/

22. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

23. ANIMAL MOVEMENT ECOLOGY February 2018) #ANME

24. AQUATIC TELEMENTRY DATA ANALYSIS USIR R (February 2018) #ATDAR

25. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL

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

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