Data analysis using R – course in Essex

August 24, 2012
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[This article was first published on Robert Grant's stats blog » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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This course is running 1-5 October at the University of Essex. There doesn’t seem to be a website but you register by writing to [email protected].

Here’s what they say in their e-mail:

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

Sounds pretty good! It will be a lot to take in but a great start to somebody’s academic year to learn all of that in the first week of October!

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