Course Overview: This course will provide an introduction to working with real-life data typical of those encountered in the field of psychology. The course will be delivered by Dr. Dale Barr and Dr. Luc Bussière, who are practicing academics in the fields of psychology and evolutionary biology respectively, with many years of expertise with R and statistical modelling as both scientists and instructors.  This five-day course will consist of series of modules (each lasting roughly half a day) covering topics including the…

Course Overview: This workshop will provide attendees with the opportunity to learn how (1) to understand; (2) run simulations of readily available Individual Based Models (IBMs); (3) analyze the outputs of IBMs; (4) parameterize IBMs, and (5) code relatively basic IBMs in R and NetLogo. Examples and applications will include cases from diverse domains and scientific disciplines such as social sciences, biology, and environmental sciences. Intended Audience This workshop is ideal for any scientists seeking an introduction as well as…

Course Overview: This workshop will provide attendees with the opportunity to learn how to use machine learning to analyze data coming from diverse data domains and scientific disciplines and without necessarily prior knowledge of the scientific discipline where the data are coming from. Attendees will learn how to use R and several R packages including classification and regression trees, ensembles and bagging, random forests, neural networks, and boosting (learning from mistakes). These techniques will be used for data classification, determining…

Course Overview: This 5-day course will cover the concepts, methods, and R tools that can be used to analyse community ecology data. The course will review data processing techniques relevant to multivariate data sets. We will cover diversity and null-model analysis, distance measures and distance based multivariate methods, clustering, classification, and dimension reduction techniques using the vegan R extension package. We will use real world data sets to motivate the analyses, e.g. describing patterns along environmental or anthropogenic disturbance gradients,…

Course Overview: This course will provide an introduction to modern multivariate techniques, with a special focus on the analysis of abundance or presence/absence data. Multivariate analysis in ecology has been changing rapidly in recent years, with a focus now on formulating a statistical model to capture key properties of the observed data, rather than transformation of data using a dissimilarity-based framework. In recent years, model-based techniques have been developed for hypothesis testing, identifying indicator species, ordination, clustering, predictive modelling, and…

Course Overview: This workshop will provide attendees with the opportunity to learn how to use machine learning to analyze data coming from diverse data domains and scientific disciplines and without necessarily prior knowledge of the scientific discipline where the data are coming from. Attendees will learn how to use R and several R packages including classification and regression trees, ensembles and bagging, random forests, neural networks, and boosting (learning from mistakes). These techniques will be used for data classification, determining…

Course Overview: Local adaptation to climate and other environmental drivers increasingly is being studied at the molecular level using high-throughput sequencing methods, with applications spanning both model and non-model organisms. At the same time, statistical tools for modeling and mapping patterns of biodiversity have seen increasing application, including to the challenge of understanding the drivers of spatial variation in adaptive genomic variation and mapping these patterns under current and future climate. This 5-day course will provide the skill set necessary…

Course Overview: This course will introduce and explain the different applications for bioacoustics to answer ecological questions. Starting with a detailed overview of the correct and most efficient methods of data collecting in the field, this course will then go on to show delegates cutting edge methods for analysing and interpreting different types of bioacoustic data. By the end of this 5-day practical course, attendees will have the capacity to set up and deploy recording devices, download acoustic data, how…

Course Overview: This 5-day workshop will introduce the development and application of Marxan type spatial planning tools to prioritize land acquisition, easements and incentives in favor of conservation. We are going to use the prioritizr framework (https://prioritizr.github.io/prioritizr/) and an example developed for the Coastal Douglas Fir Conservation Partnership (CDFCP) region by the group of Peter Arcese at UBC (http://arcese.forestry.ubc.ca/marxan-tool-cdfcp/) The reserve design problem will be introduced using examples from the BC Central Coast, Georgia Basin-Willamette Valley of BC, WA and…

Course Overview: Coming soon... Intended Audience Coming soon... Venue - PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map Availability - 20 places Duration – 5 days Contact hours – Approx. 35 hours ECT’s – Equal to 3 ECT’s Language - English Packages We offer COURSE ONLY and ACCOMMODATION PACKAGES; • COURSE ONLY – Includes lunch and refreshments. • ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday…

Course Overview: This course will cover advanced statistics regarding the analysis of data using comprehensive and state-of-the-art techniques. All methods will be illustrated using the free, open-source software package R. The course is designed for attendees that have a basic knowledge of R and elementary statistics and wish to advance this to up-to-date journal publication or conference proceedings standards. The course will cover mixed effects models, model selection and multi-model inference, generalized linear models (i.e. analysis of non-normally distributed datasets),…

Course Overview: This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them,…

Course Overview Structured population models have become a central tool to explore evolutionary and ecological processes, such as selection gradients or responses to climate change, based on field demographic data. With recent advances in theoretical ecology and computing power, these models have further evolved. Over the last decade, Integral Projection Models (IPMs), a generalization of Matrix Populations Models, have gained popularity because of their simplicity, robustness, and flexibility. This course will draw on the connections between these approaches to help…