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Social Network Analysis for Behavioural Scientists using R (SNAR01)
Course Overview: This workshop will provide students with the opportunity to learn how to use social network analysis to analyze social relational datasets such as human friendship networks or animal social networks. Attendees will learn how to use R and several R packages including igraph, sna, network, asnipe, timeordered, tsna to create network graphs, calculate descriptive network metrics, use randomization and random models to evaluate the significance of these metrics, determine graph structural properties including community structures, use QAP and…
Find out more »Introduction to Frequentist and Bayesian mixed (Hierarchical) models (IFBM01)
Course Overview: This course will cover introductory mixed or hierarchical modelling (fixed and random effects models) for real-world data sets from both a Frequentist and Bayesian perspective. These methods lie at the forefront of statistics research and are a vital tool in the scientist's toolbox. The course focuses on introducing concepts and demonstrating good practice in mixed modelling. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using both the standard lme4…
Find out more »Introduction to Bayesian data analysis for social and behavioural sciences using R and Stan (BDRS01)
Course Overview: This course provides a general introduction to Bayesian data analysis using R and the Bayesian probabilistic programming language Stan. We begin with a gentle introduction to all the fundamental principles and concepts of Bayesian data analysis: the likelihood function, prior distributions, posterior distributions, high posterior density intervals, posterior predictive distributions, marginal likelihoods, Bayes factors, etc. We will do this using some simple probabilistic models that are easy to understand and easy to work with. We then proceed to…
Find out more »Designing reliable and efficient experiments for social sciences (DRES01)
Course Overview: This course aims to help you to draw better statistical inferences from empirical research, improve the statistical questions you ask when you collect data, design better and more efficient studies, and improve your meta-analytic thinking. In practical, hands on assignments, you will learn techniques and tools that can be immediately implemented in your own research, such as thinking about the smallest effect size you are interested in, justifying your sample size, evaluate findings in the literature while keeping…
Find out more »Structural Equation Models, Path Analysis, Causal Modelling and Latent Variable Models Using R
Course Overview: This course provides a comprehensive introduction to a set of inter-related topics of widespread applicability in the social social sciences: structural equation modelling, path analysis, causal modelling, mediation analysis, latent variable modelling (including factor analysis and latent class analysis), Bayesian networks, graphical models, and other related topics. The course begins with a thorough review, both practical and theoretical, of regression modelling, particularly on general and generalized linear regression. We then turn to the topic of path analysis. At…
Find out more »Statistical modelling of time-to-event data using survival analysis: an introduction for animal behaviourists, ecologists and evolutionary biologists (TTED02)
Course Overview: Survival analysis is a set of statistical methods initially designed to analyse data giving the times at which individuals die, and assess the effect that different predictor variables have on the rate of death. However, its applications are much broader than this: it can be used to analyse any time-to-event data. Ecologists and evolutionary biologists often encounter data of this kind. Often factors influencing survival itself will be of interest. But there are many other cases, e.g. what…
Find out more »Behavioural data analysis using maximum likelihood in R (BDML02)
Course Overview: This 5-day course will involve a combination of lectures and practical sessions. Students will learn to build and fit custom models for analysing behavioural data using maximum likelihood techniques in R. This flexible approach allows a researcher to a) use a statistical model that directly represents their hypothesis, in cases where standard models are not appropriate and b) better understand how standard statistical models (e.g. GLMs) are fitted, many of which are fitted by maximum likelihood. Students will…
Find out more »Introduction to Bayesian data analysis for social and behavioural sciences using R and Stan (BDRS02)
Course Overview: This course provides a general introduction to Bayesian data analysis using R and the Bayesian probabilistic programming language Stan. We begin with a gentle introduction to all the fundamental principles and concepts of Bayesian data analysis: the likelihood function, prior distributions, posterior distributions, high posterior density intervals, posterior predictive distributions, marginal likelihoods, Bayes factors, etc. We will do this using some simple probabilistic models that are easy to understand and easy to work with. We then proceed to…
Find out more »Introduction to statistical modelling for psychologists in R (IPSY03)
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…
Find out more »ONLINE COURSE – Introduction to Bayesian hierarchical modelling using R (IBHM04) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional…
Find out more »ONLINE COURSE – Designing Efficient, Falsifiable, and Informative Experiments through Sequential Analyses and Equivalence Testing (DRES02)
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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. Course Overview: This two day course aims to help you to draw better statistical inferences from experimental research. It is common for researchers to design experiments and analyze results…
Find out more »ONLINE COURSE – Python for data science, machine learning, and scientific computing (PDMS02) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional…
Find out more »ONLINE COURSE – Generalised Linear (MIXED) (GLMM), Nonlinear (NLGLM) And General Additive Models (MIXED) (GAMM) (GNAM02) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional…
Find out more »ONLINE COURSE – Introduction to statistics using R and Rstudio (IRRS01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional…
Find out more »ONLINE COURSE – Reproducible Data Science using RMarkdown, Git, R packages, Docker, Make & Drake, and other tools (RDRP01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional…
Find out more »ONLINE COURSE – Introduction to generalised linear models using R and Rstudio (IGLM01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time +1 - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an…
Find out more »ONLINE COURSE – Introduction to mixed models using R and Rstudio (IMMR02) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time +1 - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an…
Find out more »ONLINE COURSE – Data visualization using GG plot 2 (R and Rstudio) (DVGG01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time +1 - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an…
Find out more »ONLINE COURSE – Data wrangling using R and Rstudio (DWRS01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time +1 - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an…
Find out more »ONLINE COURSE – Nonlinear Regression using Generalized Additive Models (GAMR01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. 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 – Western European Time +1 - however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an…
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