Picture source: Fig.2 from Harp et al, eClinical Medicine Volume 39, September 2021, 101045
The aim of this short course is to explain why we have to analyse variances
if we want to compare group means using ANOVA techniques. This lecture is best taken with
the Linear regression with R course.
Please note that we cannot go into the specific data analysis problems of your particular project.
Instructor: András Aszódi.
You can bring your own data to this course and run
a one-way ANOVA on it.
Your data set shall contain several groups (3 or more) of observations
that were subjected to “different levels of the same treatment”,
but only one kind of “treatment” is considered. Examples:
Because of hardware constraints, please don’t bring huge genomic datasets. The
maximal number of observations per group should be around 100.
Prepare a comma-separated-values (CSV) file with UNIX line endings (n) that
consists of columns corresponding to the groups of data. You can do this easily with Excel.
The first row shall contain the group labels.
Ideally all groups should contain the same number of observations
(a “balanced” ANOVA design). Save this file on the laptop that you bring to the course.
The training VM is protected by a firewall and other security measures.
Your training account together with all data will be deleted immediately after the course.
Number of participants: minimum 5, maximum 10.
Length: The course takes one half-day,
from 09:00 to 13:00 with two short breaks.
Please provide affiliated Organisation, and your use-case or resource use estimation (CPU-hours, GPU-hours, Memory)