Statistical Modelling in R

Venue details are sent via calendar after booking
Tuesday 23 October 2018, 09:00–16:30
Doctoral School
Doctoral School
01248 382357

This is a one day intensive course on modelling in R.

This course will be a mixture of lectures and computer practicals.

Prior knowledge: it will be assumed that participants are familiar with R. For example, inputting data, basic visualisation and data frames. Attending the introduction to R courses will provide a sufficient background. This course is suitable to a wide range of applicants.

Course outline: 

Basic hypothesis testing: examples include one-sample t-test, one-sample Wilcoxon signed-rank test, independent two-sample t-test, Mann-Whitney test, two-sample t-test for paired  samples, Wilcoxon signed-rank test. ANOVA tables: 1-way and 2-way tables.  

Simple and multiple linear regression: including model diagnostics. 

Clustering: hierarchical clustering, kmeans.  Principal components analysis: plotting and scaling data

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