“It’s easy to lie with statistics. It’s hard to tell the truth without it.”
— Andrejs Dunkels, Latvian-Swedish mathematician
The main aim of this course is to teach you to how to approach data analysis problems
with classical statistics. We focus on the intuition behind statistical methodologies
rather than on “how to run a t-test with R” (which we will also learn, by the way).
First we review the foundations (sampling theory and parameter estimation),
then we continue with hypothesis testing. The technology itself is introduced using “Student”‘s t-test
as an example, with a strong emphasis on errors (false positives, p-value distributions,
test power calculations). Finally a short “cookbook of tests” is offered.
Instructor: András Aszódi.
This course teaches the same statistical concepts as the Basic statistics with Python
training but uses the R programming language.
Online exercises are available when this course is running. Please select
the option “R stats” from the dropdown in the “Request an exercise notebook” form.
We cannot go into the specific data analysis problems of your particular project.
Furthermore, this course will not teach you bioinformatics.
In particular, no high-throughput sequencing data will be used because they are impractically large,
and not everyone on campus is working with sequencing.
You are required to be familiar with the following:
Participation in our Probability Theory with R course
is strongly recommended before taking this course.
The following skills are necessary:
If you have attended our R as a programming language training
then you are well equipped to take this course.
You can bring your own data to this course and run
a “Student”‘s t-test on it.
Please prepare
a comma-separated-values (CSV) file with UNIX line endings (n) that
consists of two columns corresponding to the two groups of data. You can do this easily
with Excel.
The first row shall contain the group labels.
The size of the two groups need not be the same.
Save the CSV file to the laptop that you will 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 two half-days,
from 09:00 to 13:00 with 2 breaks.
Please provide affiliated Organisation, and your use-case or resource use estimation (CPU-hours, GPU-hours, Memory)