BEGIN:VCALENDAR VERSION:2.0 PRODID:-//PR Statistics - ECPv6.10.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:PR Statistics X-ORIGINAL-URL:https://prstats.preprodw.com X-WR-CALDESC:Events for PR Statistics REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Europe/London BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20220327T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20221030T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20230326T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20231029T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20240331T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20241027T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20251026T010000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;VALUE=DATE:20250331 DTEND;VALUE=DATE:20250405 DTSTAMP:20260418T191439 CREATED:20211217T114057Z LAST-MODIFIED:20241128T124632Z UID:10000346-1743379200-1743811199@prstats.preprodw.com SUMMARY:ONLINE COURSE - Multivariate Analysis Of Ecological Communities Using R With The VEGAN package (VGNR07) This course will be delivered live DESCRIPTION:Delivered remotely (Finland)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Event Date \nMonday\, March 31st\, 2024\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Course Format\nThis 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. \nTime Zone\nTIME ZONE – Eastern European Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.\n \n \n \n \n \n \n \n \n \n \n About This Course\n This 5-day course will cover R concepts\, methods\, and tools that can be used to analyze community ecology data. The course will review data processing techniques relevant to multivariate data sets. We will cover diversity indices\, distance measures and distance-based multivariate methods\, clustering\, classification and ordination techniques using the R package VEGAN. We will use real-world empirical data sets to motivate analyses\, such as describing patterns along gradients of environ-mental or anthropogenic disturbances\, quantifying the effects of continuous and discrete predictors. We will emphasise visualisation and reproducible workflows as well as good programming practices. The modules will consist of introductory lectures\, guided computer coding\, and participant exercises. The course is intended for intermediate users of R who are interested in community ecology\, particularly in the areas of terrestrial and wetland ecology\, microbial ecology\, and natural resource management. You are strongly encouraged to use your own data sets (they should be clean and already structured\, see the document: “recommendation if you participate with your data”. \nThis 5-day course covers R concepts\, methods\, and tools that can be used to analyse community ecology data using (but not limited to) the R package VEGAN. We will cover :\n\n\nFundamentals of community ecology\, \nDiversity indices\, \nMethods to transform data and calculate distance measures\,\nClassifications (i.e.\, clustering methods) organise the data into synthetic groups and present them in a tree (dendrogram).\nOrdinations (i.e.\, unconstrained methods) reveal the multivariate dimension in only a few dimensions (axes).\nCanonical ordinations (i.e.\, constrained methods) test hypotheses related to multivariate patterns.\n\n\n\nIn addition the course provides lectures and practices on how to create reproducible workflows and use good programming practices in R.\n\n\n \nDuring the workshops you will follow guided computer coding exercises using either your own data or real empirical datasets to motivate analyses. Exercises include describing patterns along gradients of environmental or anthropogenic disturbance\, quantifying the effects of continuous and discrete predictors.\n \nTopics covered during the course include: terrestrial and wetland ecology\, microbial ecology\, and natural resource management\, evolution\, palaeoecology.\n \nYou are strongly encouraged to use your own datasets (they should be clean and already structured\, please contact use if you plan to do this\, we will help you to prepare the data). You will benefit from full support in applying multivariate methods to your dataset (defining of the research question\, transforming your data\, selecting the most appropriate method\, carrying out the analysis and interpreting the results).\n\n \n\n\n \n \n \n \n \n Intended Audiences\n Any researchers (PhD and MSc students\, post-docs\, primary investigators) and environmental professionals who are interested in implementing best practices and state-of-the-art methods for modelling species’ distributions or ecological niches\, with applications to biogeography\, spatial ecology\, biodiversity conservation and related disciplines.\n \n \n \n \n \n Venue\n Delivered remotely\n \n \n \n \n \n Course Details\n Availability – 20 places \nDuration – 5 days \nContact hours – Approx. 35 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English\n \n \n \n \n \n Teaching Format\n The course will be divided into theoretical lectures to introduce and explain key concepts and theories\, and practices with workshop sessions on R. \n~2 modules per day\, each module consists of ~1h30/2h lecture + coding\, break\, ~1h30/2h exercises + summary/discussion. \nThe schedule can be slightly modified according to the interest of the participants. \nThe course will take place online. \nAll the sessions will be video recorded and made available immediately on a private video hosting website as soon as possible after each 2hr session.\n \n \n \n \n \n Assumed quantitative knowledge\n We will assume that you are familiar with basic statistical concepts\, linear models\, and statistical tests (the equivalent of an undergraduate introductory statistics course will be sufficient to follow the course).\n \n \n \n \n \n Assumed computer background\n To take full advantage of this course\, minimal prior experience with R is required. Participants should be familiar with basic R syntax and commands\, know how to write code in the RStudio console and script editor\, load data from files (txt\, xls\, csv).\n \n \n \n \n \n Equipment and software requirements\n \nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n \n \n \n \n \n \nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n COURSE PROGRAMME\nClasses from 08:00 – 13:00 and 14:00 – 16:00 \nDAY 1• Module 1: Introduction to community data analysis\, basics of programming in R• Module 2: Diversity analysis\, species-abundance distributions \nClasses from 08:00 – 13:00 and 14:00 – 16:00 \nDAY 2• Module 3: Distance and transformation measures• Module 4: Clustering and classification analysis \nClasses from 08:00 – 13:00 and 14:00 – 16:00 \nDAY 3• Module 5: Unconstrained ordinations: Principal Component Analysis• Module 6: Other unconstrained ordinations \nClasses from 08:00 – 13:00 and 14:00 – 16:00 \nDAY 4• Module 7: Constrained ordinations: RDA and other canonical analysis• Module 8: Statistical tests for multivariate data and variation partitioning \nClasses from 08:00 – 13:00 and 14:00 – 16:00 \nDAY 5• Module 9: Overview of Spatial analysis\, and recent Hierarchical Modeling of Species Communities (HMSC) methods• Modules 10: Special topics and discussion\, analyzing participants’ data. \n \n \n \n \n \n \n \n Antoine Becker-Scarpitta\n \n Antoine is a community ecologist and forest ecologist working as a researcher at The French agricultural research and international cooperation organization\, working for the sustainable development of tropical and Mediterranean regions. Antoine was a postdoctoral researcher at the University of Helsinki and the Institute of Botany of the Academy of the Czech Republic. He holds a degree in Conservation Biology from the University of Paris-Sud-Orsay\, and he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity\, particularly on the forest and Arctic vegetation. Antoine has taught community ecology\, plant ecology and evolution\, linear and multivariate statistics assisted on R. \nResearchGate \nGoogle Scholar \nORCID \nGitHub URL:https://prstats.preprodw.com/course/multivariate-analysis-of-ecological-communities-using-r-with-the-vegan-package-vgnr07/ LOCATION:Delivered remotely (Finland)\, Western European Time\, United Kingdom CATEGORIES:All Live Courses,Home Courses,Live Online Courses ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/02/VGNR04R.png GEO:55.378051;-3.435973 END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20250226 DTEND;VALUE=DATE:20250301 DTSTAMP:20260418T191440 CREATED:20220218T204056Z LAST-MODIFIED:20241216T161521Z UID:10000309-1740528000-1740787199@prstats.preprodw.com SUMMARY:ONLINE COURSE - Community Analytics in Ecology and Evolutionary Biology for Beginners (CAFB01) This course will be delivered live DESCRIPTION:Delivered remotely (Finland)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Event Date \nWednesday\, February 26th\, 2022\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Course Format\nThis 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. \nTime Zone\nTIME ZONE – Eastern Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you). \n \n \n \n \n \n \n \n \n \n \n About This Course\n This community analytics course is designed for students who have recently started their projects or researchers who are starting using the R ecosystem. During this three-day course\, we will cover the basic concepts of multivariate analysis and their implementation in R. This course is a complement to the PR Statistic offering allowing also beginners and non-programmers to discover the statistical tools needed to analyze an ecological dataset in research\, natural resource management or conservation context. This course is not geared toward any particular taxonomic group or ecological system. \nWe will cover diversity indices\, distance measures and multivariate distance-based methods\, clustering\, classification\, and ordination techniques. We will focus on the concept of the methods and their implementation on R using different R packages. We will use real-world examples to implement analyses\, such as describing patterns along gradients of environmental or anthropogenic disturbances\, quantifying the effects of continuous and discrete predictors\, data mining. The course will consist of lectures\, work on R code scripts\, and exercises for participants. \nPR stats also deliver a more advanced course on analysing community data \nONLINE COURSE – Multivariate Analysis Of Ecological Communities Using R With The VEGAN package (VGNR07) \n \n \n \n \n \n Intended Audiences\n Any researchers (PhD and MSc students\, post-docs\, primary investigators) and environmental professionals who are interested in learning multivariate statistics. \n \n \n \n \n \n Venue\n Delivered remotely \n \n \n \n \n \n Course Details\n Time Zone – Eastern Standard Time \nAvailability – 20 places \nDuration – 3 days \nContact hours – Approx. 21 hours \nECT’s – Equal to 2 ECT’s \nLanguage – English \n \n \n \n \n \n Teaching Format\n The course will be divided into theoretical lectures to introduce and explain key concepts and theories\, and practices with workshop sessions on R. \n~2 modules per day\, each module consists of ~1h30/2h lecture + coding\, break\, ~1h30/2h exercises + summary/discussion. \nThe schedule can be slightly modified according to the interest of the participants. \nThe course will take place online. All the sessions will be video recorded and made available immediately on a private video hosting website as soon as possible after each 2hr session. \n \n \n \n \n \n Assumed quantitative knowledge\n A basic knowledge of statistics is required. \n \n \n \n \n \n Assumed computer background\n The participants are required to have some previous experience with R and should know the main data types and how to run commands to create basic plots. \n \n \n \n \n \n Equipment and software requirements\n \nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. \n\n\n\n\n\nParticipants should be able to install additional software on their own computer during the course (please make sure you have administration rights to your computer).  \n\n\n\n\n\n\nA large monitor and a second screen\, although not absolutely necessary\, could improve the learning experience. Participants are also encouraged to keep their webcam active to increase the interaction with the instructor and other students. \n\n\n\n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited. \n \n \n \n \n \n \nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n COURSE PROGRAMME\nThis 3-day course will explores the nature of community data\, and how they are transformed and analysed them in the context of ecological research projects. The course will explore the numerical tools used to describe ecological communities\, with a particular focus on R. \nWednesday 26th – Classes from 09:00-17:00 \n– Classifications (i.e.\, clustering methods) organise the data into synthetic groups and present them in a tree (dendrogram). \nThursday 27th – Classes from 09:00-17:00 \n– Ordinations (i.e.\, unconstrained methods) reveal the multivariate dimension in only a few dimensions (axes). \nFriday 28th – Classes from 09:00-17:00 \n– Canonical ordinations (i.e.\, constrained methods) test hypotheses related to multivariate patterns. \n \n \n \n \n \n Course Instructor\n \n  \n  \n  \nDr. Antoine Becker-Scarpitta\nWorks at – University of HelsinkTeaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03) \nAntoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay\, and from the Natural History Museum of Paris\, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology\, plant ecology and evolution\, linear and multivariate statistics assisted on R. URL:https://prstats.preprodw.com/course/community-analytics-in-ecology-and-evolutionary-biology-for-beginners-cafb01/ LOCATION:Delivered remotely (Finland)\, Western European Time\, United Kingdom CATEGORIES:Home Courses,Live Online Courses ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/02/IMAE01.png GEO:55.378051;-3.435973 END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/London:20220406T133000 DTEND;TZID=Europe/London:20220406T143000 DTSTAMP:20260418T191440 CREATED:20220221T223934Z LAST-MODIFIED:20220406T095735Z UID:10000358-1649251800-1649255400@prstats.preprodw.com SUMMARY:FREE SEMINAR - Introduction To Multivariate Analysis In Ecology And Evolutionary Biology using R (IMAE01S) This course will be delivered live DESCRIPTION:Delivered remotely (Finland)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Event Date \nOnline registration has now closed\, please email oliverhooker@prstatistics.com to be added to the seminar or to receive a link to the recording\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nFree seminar \n\n\nThis is a free ~30 minute seminar including a Q and A session at the end for our up-coming course “Introduction to Multivariate Analysis in Ecology and Evolutionary Biology using R” \n\n\nTime \n\n\n13:30-14:00 Eastern European Standard Time \n\n\nSpeaker \n\n\nCourse Instructor Dr. Antoine Becker-Scarpitta \n\n\nAbout this course \nThis community analytics course is designed for students who have recently started their projects or researchers who are starting using the R ecosystem. During this three-day course\, we will cover the basic concepts of multivariate analysis and their implementation in R. This course is a complement to the PR Statistic offering allowing also beginners and non-programmers to discover the statistical tools needed to analyze an ecological dataset in research\, natural resource management or conservation context. This course is not geared toward any particular taxonomic group or ecological system. \nWe will cover diversity indices\, distance measures and multivariate distance-based methods\, clustering\, classification\, and ordination techniques. We will focus on the concept of the methods and their implementation on R using different R packages. We will use real-world examples to implement analyses\, such as describing patterns along gradients of environmental or anthropogenic disturbances\, quantifying the effects of continuous and discrete predictors\, data mining. The course will consist of lectures\, work on R code scripts\, and exercises for participants. \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n \n \n \n \n \n If you are unsure about course suitability\, please get in touch by email to find out more \ninfo@clovertraining.co.uk URL:https://prstats.preprodw.com/course/introduction-to-multivariate-analysis-in-ecology-and-evolutionary-biology-using-r-imae01s/ LOCATION:Delivered remotely (Finland)\, Western European Time\, United Kingdom CATEGORIES:All Live Courses,Free Seminars,Home Seminars ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/02/IMAE01.png GEO:55.378051;-3.435973 END:VEVENT END:VCALENDAR