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July 2018
£220.00 - £530.00

Social Network Analysis for Behavioural Scientists using R (SNAR01)

2nd July 2018 - 5th July 2018
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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October 2018
£275.00 - £500

Introduction to Frequentist and Bayesian mixed (Hierarchical) models (IFBM01)

8th October 2018 - 12th October 2018
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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December 2018
£275.00 - £510.00

Introduction to Bayesian data analysis for social and behavioural sciences using R and Stan (BDRS01)

3rd December 2018 - 7th December 2018
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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February 2019
£220.00 - £460.00

Designing reliable and efficient experiments for social sciences (DRES01)

4 February 2019 - 7 February 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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July 2019
£275 - £520.00

Introduction to Bayesian hierarchical modelling using R (IBHM03)

8 July 2019 - 12 July 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

Course Overview: This course will cover introductory hierarchical modelling for real-world data sets from a 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 hierarchical models. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using the Bayesian modelling software Jags and Stan through the R…

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September 2019
£275.00 - £520.00

Generalised Linear (MIXED) (GLMM), Nonlinear (NLGLM) And General Additive Models (MIXED) (GAMM) (GNAM01)

9 September 2019 - 13 September 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

Course Overview: This course provides a general introduction to nonlinear regression analysis, covering major topics including, but not limited to, general and generalized linear models, generalized additive models, spline and radial basis function regression, and Gaussian process regression. We approach the general topic of nonlinear regression by showing how the powerful and flexible statistical modelling framework of general and generalized linear models, and their multilevel counterparts, can be extended to handle nonlinear relationships between predictor and outcome variables. We begin…

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£275.00 - £540.00

Structural Equation Models, Path Analysis, Causal Modelling and Latent Variable Models Using R

16 September 2019 - 20 September 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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£275.00 - £550

Python for data science, machine learning, and scientific computing (PDMS01)

23 September 2019 - 27 September 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

Course Overview: Python is one of the most widely used and highly valued programming languages in the world, and is especially widely used in data science, machine learning, and in other scientific computing applications. This course provides both a general introduction to programming with Python and a comprehensive introduction to using Python for data science, machine learning, and scientific computing. The major topics that we will cover include the following: the fundamentals of general purpose programming in Python; using Jupyter…

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October 2019
£275.00 - £550.00

Statistical modelling of time-to-event data using survival analysis: an introduction for animal behaviourists, ecologists and evolutionary biologists (TTED02)

14 October 2019 - 18 October 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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November 2019
£275.00 - £560.00

Behavioural data analysis using maximum likelihood in R (BDML02)

4 November 2019 - 8 November 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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£275.00 - £560.00

Introduction to Bayesian data analysis for social and behavioural sciences using R and Stan (BDRS02)

4 November 2019 - 8 November 2019
PS statistics head office, 53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom

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…

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