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 [log in to unmask] 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 [log in to unmask] with any questions.

UPCOMING COURSES LIVE ONLINE COURSES

Introduction To Multivariate Analysis In Ecology And Evolutionary Biology (IMAE01)
https://www.prstatistics.com/course/online-course-introduction-to-multivariate-analysis-in-ecology-and-evolutionary-biology-imae01/

Multivariate Analysis Of Ecological Communities Using R With The VEGAN package (VGNR04)
https://www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-using-r-with-the-vegan-package-vgnr04/

Bioacoustics For Ecologists: Hardware, Survey design And Data analysis (BIAC03)
https://www.prstatistics.com/course/bioacoustics-for-ecologists-hardware-survey-design-and-data-analysis-biac03/

Species Distribution Modelling With Bayesian Statistics Using R (SDMB04)
https://www.prstatistics.com/course/online-course-species-distribution-modelling-with-bayesian-statistics-in-r-sdmb04/

Introduction to Aquatic Acoustic Telemetry (IAAT02)
https://www.prstatistics.com/course/online-course-introduction-to-aquatic-acoustic-telemetry-iaat02/

Time Series Data Analysis (TSDA02)
https://www.prstatistics.com/course/online-course-time-series-data-analysis-tsda02/

Introduction to generalised linear models using R and Rstudio (IGLM05)
https://www.prstatistics.com/course/introduction-to-generalised-linear-models-using-r-and-rstudio-iglm05/

Bayesian Data Analysis (BADA02) 
https://www.prstatistics.com/course/bayesian-data-analysis-bada02/

Nonlinear Regression using Generalized Additive Models (GAMR02)
https://www.prstatistics.com/course/nonlinear-regression-using-generalized-additive-models-gamr02/

Ecological niche modelling using R (ENMR04)
https://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr04/

Stable Isotope Mixing Models using SIBER, SIAR, MixSIAR (SIMM09)
https://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm09/


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

FREE 1 DAY INTRO TO R AND R STUDIO (FIRR01R)
https://www.prstatistics.com/course/free-1-day-intro-to-r-and-r-studio-firr01r/

Introduction To Statistics Using R And Rstudio (IRRS03R)
https://www.prstatistics.com/course/introduction-to-statistics-using-r-and-rstudio-irrs03r/

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)
https://www.prstatistics.com/course/introduction-to-mixed-models-using-r-and-rstudio-immr05r/

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

Introduction To Machine Learning And Deep Learning Using R (IMDL02R)
https://www.prstatistics.com/course/introduction-to-machine-learning-and-deep-learning-using-r-imdl02r/

Model Selection And Model Simplification (MSMS02R)
https://www.prstatistics.com/course/model-selection-and-model-simplification-msms02r/

Reproducible Data Science Using RMarkdown, Git, R Packages, Docker, Make & Drake And Other Tools (RDRP01R)
https://www.prstatistics.com/course/reproducible-data-science-using-rmarkdown-git-r-packages-docker-make-drake-and-other-tools-rdrp01r/

Data Wrangling Using R And Rstudio (DWRS02R)
https://www.prstatistics.com/course/data-wrangling-using-r-and-rstudio-dwrs02r/

Data visualization using GG plot 2 (R and Rstudio) (DVGG02R)
https://www.prstatistics.com/course/data-visualization-using-gg-plot-2-r-and-rstudio-dvgg02r/

Introduction To Data Wrangling And Data Visualization Using R (DWDV01R)
https://www.prstatistics.com/course/introduction-to-data-wrangling-and-data-visualization-using-r-dwdv01r/


Bayesian

Fundamentals of Bayesian Data Analysis using R (FBDA01R)
https://www.prstatistics.com/course/introduction-fundamentals-of-bayesian-data-analysis-statistics-using-r-fbda01r/

Bayesian Approaches To Regression And Mixed Effects Models Using R And brms (BARM01R)
https://www.prstatistics.com/course/bayesian-approaches-to-regression-and-mixed-effects-models-using-r-and-brms-barm01r/

Bayesian Hierarchical Modelling Using R (IBHM05R)
https://www.prstatistics.com/course/bayesian-hierarchical-modelling-using-r-ibhm05r/

Bayesian Data Analysis (BADA01R)
https://www.prstatistics.com/course/bayesian-data-analysis-bada01r/

Introduction To Stan For Bayesian Data Analysis (ISBD01R)
https://www.prstatistics.com/course/introduction-to-stan-for-bayesian-data-analysis-isbd01r/


Spatial / Spatial Ecology

Introduction To Spatial Analysis Of Ecological Data Using R (ISPE04R)
https://www.prstatistics.com/course/introduction-to-spatial-analysis-of-ecological-data-using-r-ispe04r/

Making Beautiful And Effective Maps In R (MAPR03R)
https://www.prstatistics.com/course/making-beautiful-and-effective-maps-in-r-mapr03r/

Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJ02R)
https://www.prstatistics.com/course/adapting-to-the-recent-changes-in-r-spatial-packages-sf-terra-proj-library-proj02r/

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)
https://www.prstatistics.com/course/advanced-ecological-niche-modelling-using-r-anmr01r/

Model-Based Multivariate Analysis Of Abundance Data Using R (MBMV03R)
https://www.prstatistics.com/course/model-based-multivariate-analysis-of-abundance-data-using-r-mbmv03r/

Movement Ecology (MOVE04R)
https://www.prstatistics.com/course/movement-ecology-move04r/


Molecular Ecology

Introduction To Eco-Phylogenetics And Comparative Analyses Using R (ECPH01R)
https://www.prstatistics.com/course/introduction-to-eco-phylogenetics-and-comparative-analyses-using-r-ecph01r/

Fundamentals Of Population Genetics Using R (FOPG01R)
https://www.prstatistics.com/course/fundamentals-of-population-genetics-using-r-fopg01r/


Miscellaneous Ecology

Stable Isotope Mixing Models Using SIBER, SIAR, MixSIAR (SIMM08R)
https://www.prstatistics.com/course/stable-isotope-mixing-models-using-siber-siar-mixsiar-simm08r/

Bioacoustics For Ecologists: Hardware, Survey Design and Data Analysis (BIAC02R)
https://www.prstatistics.com/course/bioacoustics-for-ecologists-hardware-survey-design-and-data-analysis-biac02r/


Python

Introduction to Python and Programming in Python (PYIN03R)
https://www.prstatistics.com/course/introduction-to-python-and-programming-in-python-pyin03r/

Introduction To Scientific, Numerical And Data Analysis Programming In Python (PYSC02R)
https://www.prstatistics.com/course/introduction-to-scientific-numerical-and-data-analysis-programming-in-python-pysc02r/

Machine Learning and Deep Learning Using Python (PYML02R)
https://www.prstatistics.com/course/machine-learning-and-deep-learning-using-python-pyml02r/

Python For Data Science, Machine Learning And Scientific Computing (PDMS02R)
https://www.prstatistics.com/course/python-for-data-science-machine-learning-and-scientific-computing-pdms02r/

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