Seminars for 2016/17


01 October 2012: Data Analysis using R (Short courses)

Dr Werner Adler and Dr Benjamin Hofner from Institute of Medical Informatics, Biometry and Epidemiology, University of Erlangen-Nuremberg

At 09:30 in Lab A.

Proficio programme of the University of Essex 

Short Course: Data Analysis using R

The introductory R course covers basic statistical concepts and briefly explains theoretical backgrounds. The open-source software package R (www.r-project.org) is introduced as a versatile tool to use these concepts for data analysis with a focus on biomedical applications. Target Audience: Postgraduate students; Continuous professional development (CPD).

Date: 01 October 2012 – 05 October 2012
Fees: £660 (academic; non UoE PhD student); £964 (commercial); £330 (UoE PhD student)

Registration via maths@essex.ac.uk by 20 September 2012 (Limited number of places!)

Lecturers:

Dr Werner Adler (University of Erlangen-Nuremberg; Co-author of R-packages Daim and survAUC);

Dr Benjamin Hofner (University of Erlangen-Nuremberg; Author of R-packages gamboostLSS and CoxFlexBoost; Co-author of R-package mboost)


Course contents:
Day 1: Introduction to R (9.30am - 1pm course, 2.30pm-5pm lab)
• Concepts of R (graphical user interface (GUI), editors, work flow, help system)
• Basic Programming (objects, functions, vectors, matrices, data sets)
• Examples and Hands-on Training

Day 2: Introduction to Statistics & Graphics (9.30am - 1pm course, 2.30pm-5pm lab)
• Data Management
• Descriptive Statistics
• Graphics
• Examples and Hands-on Training

Day 3: Diagnostic and Statistical Tests (9.30am - 1pm course, 2.30pm-5pm lab)
• Diagnostic Tests (quality of diagnostic tests, ROC analysis)
• Statistical Tests (binomial test, one-sample t-test, one-sample Wilcoxon signed-rank test, independent two-sample t-test, Mann-Whitney U test, two-sample t-test for paired samples, Wilcoxon signed-rank test [for dependent samples], Χ2-test, logrank test)
• Examples and Hands-on Training

Day 4: Regression Analysis (9.30am - 1pm course, 2.30pm-5pm lab)
• Linear Regression Models (incl. model diagnostics and variable selection)
• ANOVA (incl. prognosis and model diagnostics)
• Logistic Regression (short outlook)
• Examples and Hands-on Training

Day 5: (optional 9.30am - 1pm lab)
• Optional discussion of statistical data analysis issues of participants
• Examples and Hands-on Training

Course Prerequisites: Interest in statistical data analysis, basic statistical knowledge

Further Reading:
• Adler, J. 2010: R in a nutshell; O’Reilly.
• Dalgaard, P. 2002: Introductory Statistics with R; Springer.
• Everitt, B.S. and Hothorn, T. 2006: A Handbook of Statistical Analysis using R; Chapman & Hall.
• Kabacoff, R.I. 2011: R in Action - Data Analysis and Graphics with R; Manning Publications Co.
• Venables, W.N. and Ripley, B.D. 2002: Modern Applied Statistics with S; Springer.
• Verzani, J. 2002: simpleR – Using R for Introductory Statistics;
URL: http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf

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