Dear colleagues, Registration is open for the workshop "R Without Fear: Applied R for Biologists", September 21-25, 2015. Instructor: Dr. Jordi Moya-Laraño (Estación Experimental de Zonas Áridas - CSIC, Spain).
PLACE: Facilities of the Centre de Restauració i Interpretació Paleontologica, Els Hostalets de Pierola, Barcelona (Spain). WEBPAGE: http://www.transmittingscience.org/courses/stats/applied-r-for-bio/ PROGRAM: Introduction to the R working environment. - Variable types in R. - Statistical populations and samples through working examples. - Measurements of central tendency and variability. - Precision, accuracy and bias. - Hypothesis testing: Falsability, Type-I and II errors and statistical power. - Correlation and simple regression. - P-value vs. effect magnitude. - Linear Models: Residuals, assumptions and interpretation. - Explained vs. unexplained variance of a model (the coefficient of determination). - Building functions in R. - Introduction to graphics in R. - The concept of partial effect: Partial regression and correlation. - General Linear Models (GLM). - Curve fitting in linear models and General Additive Models (GAMs). - The problem of spatial autocorrelation in ecology and evolution. - Multicolinearity: When is there a problem? - Additive vs. multiplicative effects: Checking and plotting interactions. - Introduction to General and Generalized Linear Mixed Models (GLMM). - Fixed vs. Random effects and implications for analysis: Main R functions. - Introduction to Bayesian statistics: The function MCMCglmm. - Practical examples in evolutionary ecology: The study of natural selection. Applications of linear models for quantitative genetics. - Student’s case studies. Please feel free to distribute this information between your colleagues if you consider it appropriate. With best regards Soledad De Esteban-Trivigno, Ph.D. Transmitting Science www.transmittingscience.org ---------------------------------------------- CLASS-L list. Instructions: http://www.classification-society.org/csna/lists.html#class-l
