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July 2018
£220.00 - £530.00

Social Network Analysis for Behavioural Scientists using R (SNAR01)

2 July 2018 - 5 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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January 2019
£275.00 - £510.00

Statistical modelling of time-to-event data using survival analysis: an introduction for animal behaviourists, ecologists and evolutionary biologists (TTED01)

21st January 2019 - 25th January 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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February 2019
£220.00 - £460.00

Designing reliable and efficient experiments for social sciences (DRES01)

4th February 2019 - 7th 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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