Master's and PhD Programs, Summer Schools, Professional Training, Jobs, Conferences and Scholarships
We help students, researchers, and professionals working in Statistics & Data Science to reach their academic and professional goals.
Latest Listings
Scala for Statistical Computing and Data Science
This course is aimed at statisticians and data scientists already familiar with a dynamic programming language (such as R, Python or Octave). Scala is a free modern, powerful, strongly-typed, functional programming language. In particular, it is fast...
Programming with R
The benefit of using a programming language such as R is that we can automate repetitive tasks. This course covers the fundamental techniques such as functions, for loops and conditional expressions. By the end of this course, you will understand wha...
Regression Models: A Hands-on Approach using R
OverviewRegression is a powerful technique for studying relationships between quantitative variables. Summarising relationships by the most appropriate equation (modelling) is very quick when using a statistical package. It is also easy to progress f...
Introduction to Bayesian Statistics for Scientists using R
OverviewBayesian statistics have become very popular in recent years. Modern software has made this possible and Bayesian methods are now applied in a wide range of scientific application areas from medicine to ecology. This course provides an introd...
What Sample Size Do I Need? with R
OverviewChoosing an appropriate sample size is a common problem and should be given due consideration in any research proposal, as an inadequate sample size invariably leads to wasted resources. Hence objective sample size determination is increasing...
Introduction to Linear Mixed Models using R
OverviewMixed modelling is a modern and powerful data analysis tool for modelling clustered data, typically used for modelling data collected in trials where the levels of a factor are considered to be a random selection from a wider pool, or in the ...
Survival Analysis for Medical and Health Professionals using R
OverviewSurvival data arise in many medical areas. Examples include time to death after an operation, time to recovery from an accident, and duration of pain relief. One particular aspect of time-to-event data is censoring, where the time to an event...
Data Scientist
Job ref: RLS004_1610127527 Location: Royal Leamington Spa Salary: Up to £33,696 per annum Start date: ASAP Fixed term contract We're currently seeking Data Scientists based in and around Leamington Spa with experienced of processing large scientific ...
Royal Leamington Spa, United Kingdom
Principal Data Scientist
Principal Data Scientist Health Economics and Outcomes Research (HEOR) Ltd is an independent consultancy specialising in the application of health economic techniques to support pharmaceutical pricing, health technology assessment (HTA) and value ass...
Cardiff, United Kingdom
Birmingham, United Kingdom
Webinar: The Catalogue of Mental Health Measures: Discovering the depths of mental health data in UK longitudinal studies
This webinar is jointly organised by the UK Data Service, The University of Essex, and the Institute of Psychiatry, Psychology & Neuroscience, Kings College London.This webinar will introduce the new Catalogue of Mental Health which provides a...
PhD student in Statistics in collaboration with IFAU
Uppsala University is a comprehensive research-intensive university with a strong international standing. Our mission is to pursue top-quality research and education and to interact constructively with society. Our most important assets are all the i...
Uppsala, Sweden
HTA & Modelling Courses 2021
The Health Economics & Health Technology Assessment (HEHTA) research group at the University of Glasgow is now taking bookings for its 2021 courses.Semester two is extremely popular, so we urge you to book early. We offer discounts for groups, ac...
Python for Data Visualisation
Python has a number of packages for the effective creation of graphics to communicate your data insights. This one day course will examine a range of packages for building impactful visualisations. During the training session, we'll cover the main Py...
ANOVA/GLMs with SPSS
23 March 2021–24 March 2021, 9:30 am–1:00 pm This course will introduce delegates to the basic principles of ANOVA, and how to choose, run, interpret, and report a variety of ANOVA models. The course takes a hands-on approach to learning, with SPSS s...
Chi-square and Beyond for 2x2 Tables
17 March 2021–18 March 2021, 9:30 am–1:00 pm This course aims to demystify the range of statistics that can be used to summarise the associations between two binary variables. We move on from the standard chi-square test to investigate other options ...
Introduction to Bayesian Analysis
15 March 2021–16 March 2021, 9:30 am–1:00 pm This course focuses on the principles of Bayesian analysis with the aim to enable participants to apply Bayesian methods on their own research and understand other people's results via Bayesian analysis. N...
Introduction to Dealing with Missing Data
08 March 2021–10 March 2021, 9:30 am–1:00 pm This course looks at the problem of missing data in research studies in detail. Reasons and different types of missing data are discussed as well as bad and good methods of dealing with them. Book Now (Mai...
Overview of Regressions with R
01 March 2021–04 March 2021, 9:30 am–1:00 pm This two-day course provides an overview of the most commonly applied types of regression modelling and their application in R. NOTE: Due to the coronavirus outbreak, all courses will now be delivered onli...
Introduction to Survival/Time-to-Event Data Analysis
24 February 2021–25 February 2021, 9:30 am–1:00 pm This course introduces the concept of modelling time-to event data, commonly known as survival analysis. Log-rank tests and Cox proportional hazard regression models are used to determine association...
Introduction to Regression Analysis
16 February 2021–19 February 2021, 9:30 am–1:00 pm This course provides an overview of different regression types and details the application of multiple linear regression. The main course focuses on the theory behind regression analysis, in particul...
Introduction to SPSS
12 February 2021, 9:00 am–5:00 pm This course offers an introduction to the uses and functions of the statistical software SPSS including data entry and editing, and the basics of analyses and graphs. The course is ideally suited to those with little...
Introduction to Meta-Analysis
01 February 2021–03 February 2021, 9:30 am–1:00 pm This course provides an overview of meta-analysis from a statistician's point of view, with an optional half day workshop in R. NOTE: Due to the coronavirus outbreak, all courses will now be delivere...
Introduction to Research Methods and Statistics
25 January 2021–29 January 2021, 9:30 am–5:00 pm This course offers a comprehensive introduction to the fundamental aspects of research methods and statistics. From study design, data types, and graphs, through to choice and interpretation of statist...
Git For Me
A one day introduction to Git with RStudio. When working on data analysis projects version control is essential. Even on small projects, tracking the progress of your project’s code-base has many advantages and makes collaboration much easier. Fortun...
Next Steps in the Tidyverse
The tidyverse is essential for any statistician or data scientist who deals with data on a day-to-day basis. By focusing on small key tasks, the {tidyverse} suite of packages removes the pain of data manipulation. This course takes the next steps in ...
Getting to Grips with the Tidyverse
The {tidyverse} is essential for any data scientist who deals with data on a day-to-day basis. By focusing on small key tasks, the {tidyverse} suite of packages removes the pain of data manipulation. The {tidyverse} allows you to Import data from dat...
Introduction to Bayesian Inference
The capturing and quantification of uncertainty is a very important aspect of model-fitting and parameter inference. Bayesian inference represents a fully-probabilistic approach to parameter inference, allowing a practitioner to quantify their uncert...
Introduction to Bayesian Inference using RStan
Despite the promise of big data, inferences are often limited not by the size of data but rather by its systematic structure. Only by carefully modelling this structure can we take full advantage of the data -- big data must be complemented with big ...
Statistical Modelling with R
From the very beginning, R was designed for statistical modelling. Out of the box, R makes standard statistical techniques easy. This course covers the fundamental modelling techniques. We begin the day by revising hypotheses tests, before moving ont...
Strategy & Analytics Graduate Scheme
Become part of the team We have designed three schemes which reflect the nature of how we work with our clients and the challenges they face. Within each 18-month scheme you will have the opportunity to rotate through up to three of our Capability te...
London, United Kingdom
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Featured Listings
UK Data Service, The University of Essex, and the Institute of Psychiatry, Psychology & Neuroscience, Kings College London
online
February 11, 2021
