[R-sig-eco] Reproducible and collaborative data analysis with R (RACR01)

Oliver Hooker o||verhooker @end|ng |rom pr@t@t|@t|c@@com
Fri Jul 29 14:32:17 CEST 2022


Please feel free not to post if this is not considered relevant.


ONLINE COURSE – Reproducible and collaborative data analysis with R
(RACR01) This course will be delivered live



https://www.prstatistics.com/course/reproducible-and-collaborative-data-analysis-with-r-racr01/



5th - 7th September



Please feel free to share!



COURSE FORMAT

This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and
coaching attendees through the accompanying computer practical’s via video
link, a good internet connection is essential.



TIME ZONE

CET – however all sessions will be recorded and made available allowing
attendees from different time zones to follow. Please email
oliverhooker using prstatistics.com for full details or to discuss how we can
accommodate you).



ABOUT THIS COURSE

The computational part of a research is considered reproducible when other
scientists (including ourselves in the future) can obtain identical results
using the same code, data, workflow and software. Research results are
often based on complex statistical analyses which make use of various
software. In this context, it becomes rather difficult to guarantee the
reproducibility of the research, which is increasingly considered a
requirement to assess the validity of scientific claims. Moreover,
reproducibility is not only important for findings published in academic
journals. It also becomes relevant for sharing analyses within a team, with
external collaborators and with one’s supervisor. During this three-day
course, the participants will be introduced to a suite of tools they can
use in combination with R to make reproducible the computational part of
their own research. A strong emphasis is given to collaboration, and
participants will learn how to set up a project to work with other people
in an efficient way.

On day 1 the participants learn about the most important aspects that make
research reproducible, which go beyond simply sharing R code. This includes
problems arising from the use of different packages versions, R versions,
and operating systems. The concept of research compendium is introduced and
proposed as general framework to organise any research project. Day 2 is
dedicated to version control with Git and GitHub which are fundamental
tools for keeping track of code changes and for collaborating with other
people on the same project. We will cover both, basic and more advanced
features, like tagging, branching, and merging. On day 3 the participants
are introduced to literate programming using RMarkdown with the focus on
writing a scientific article. The aim is to bind the outputs of the R
analysis (i.e. results, tables, and figures) together with the text of the
article. Participants will also learn how to use templates to fulfil
requirements of different journals.



Please email oliverhooker using prstatistics.com with any questions.



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PR statistics have over 30 courses archived and available on demand on our
recorded courses page

https://www.prstatistics.com/recorded-courses/



Moving our courses online due to the COVID pandemic has allowed us to
archive all our previous courses and offer them in a recorded format. This
is ideal for; People with busy schedules who can’t take long periods off
work to attend workshops; Allows attendees to work at their own pace with
email support; Suitable for people from all timezones. The recordings are
taken from our Live Online Courses which ensures all materials and software
packages are constantly up-to-date.



‘General’ Courses



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https://www.prstatistics.com/course/free-1-day-intro-to-r-and-r-studio-firr01r/



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Introduction To Generalised Linear Models Using R And Rstudio (IGLM04R)

https://www.prstatistics.com/course/introduction-to-generalised-linear-models-using-r-and-rstudio-iglm04r/



Introduction To Mixed Models Using R And Rstudio (IMMR05R)

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Nonlinear Regression Using Generalized Additive Models (GAMR01R)

https://www.prstatistics.com/course/nonlinear-regression-using-generalized-additive-models-gamr01r/



Hidden Markov and State Space Models Using R (HMSS01R)

Coming soon



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https://www.prstatistics.com/course/introduction-to-machine-learning-and-deep-learning-using-r-imdl02r/



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Data visualization using GG plot 2 (R and Rstudio) (DVGG02R)

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Bayesian



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Bayesian Approaches To Regression And Mixed Effects Models Using R And brms
(BARM01R)

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Bayesian Hierarchical Modelling Using R (IBHM05R)

https://www.prstatistics.com/course/bayesian-hierarchical-modelling-using-r-ibhm05r/



Bayesian Data Analysis (BADA01R)

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Introduction To Stan For Bayesian Data Analysis (ISBD01R)

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Spatial / Spatial Ecology



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Adapting to the recent changes in R spatial packages (sf, terra, PROJ
library) (PROJ02R)

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Species Distribution Modeling using R (SDMR04R)

https://www.prstatistics.com/course/species-distribution-modeling-using-r-sdmr04r/



Ecological niche modelling using R (ENMR03R)

https://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr03r/



Advanced Ecological Niche Modelling Using R (ANMR01R)

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Model-Based Multivariate Analysis Of Abundance Data Using R (MBMV03R)

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Movement Ecology (MOVE04R)

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Molecular Ecology



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https://www.prstatistics.com/course/introduction-to-eco-phylogenetics-and-comparative-analyses-using-r-ecph01r/



Fundamentals Of Population Genetics Using R (FOPG01R)

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Miscellaneous Ecology



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(BIAC02R)

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Python



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-- 

Oliver Hooker PhD.
PR statistics

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