IRTG 1054 Workshop - Data Analysis with R

Workshop Details

Date: Wednesday, 04 December - Friday, 06 December 2019 (3 days)
Venue: BMC, Großhaderner Str. 9, Planegg-Martinsried
Language: English
Trainer: Rick Scavetta, Scavetta Academy

Registration

If you are interested in this workshop and/or would like to register for it, please send an email to Katharina Frank by Sunday, 27 October 2019.

• Please note that workshop slots will be allocated according to IRTG 1054 lecture and SFB 1054 seminar attendance.
• Please only register for the workshop if you are sure that you will be able to participate in the entire event.
  

The Target Audience

This workshop is targeted towards researchers in all areas with quantiative data. Is assumes no prior programming knowledge. Nonetheless, participants should be computer literate, including appropriate typing speed and have prepared some data to work on.

Workshop content

Description

R is an open-source cross-platform software tool that combines data manipulation, statistical modelling and visualisation.

The Data Analysis workshop enables laboratory-based life scientists to use the R statistical programming environment to analyse their own data. This workshop focuses on data manipulation and biostatistics modelling using relevant examples from the life sciences.

Using plenty of hands-on exercises, participants will learn about:

The most common data structures and functions in R,
How to manage and ask specific questions of their data, and
How to use the results of statistical tests.

Packages (e.g. the tidyverse) and paradigms (vectorization) that make R well-suited to data manipulation, as well as common beginner pit-falls, will be introduced.

Basic visualisations will be covered, but will be treated in more depth in the separate Data Visualization workshop.

Methods for dealing with missing data will be broached at various parts int he workshop.

Approximately one third of class time is dedicated to having the students work on their own data-sets under the supervision of the instructor. The goal is to develop data analysis solutions as part of the workshop.

Extra material is provided in the reference book for specific problems, e.g. pattern matching with regular expressions, and control structures (e.g. loops and conditional statements). Participants will be provided with all data-sets and access to the book after the workshop to continue working on these case studies.

Requirements

The workshop does not set out to teach biostatistics, although how to execute various descriptive and inferential statistics in an efficient manner will be covered. Participants should be comfortable with computing and be familiar with basic biostatistics to take full advantage of the workshop.

Participants are asked to bring in their own data sets and computers for practical work.

The workshop takes a practical, hands-on approach to learning data analysis, but does not set-out to teach biostatistics. The implementation of basic descriptive statistics, in addition to estimation and inference methods and linear models, will be covered. Participants should be comfortable with computing and be familiar with basic biostatistics to take full advantage of the workshop. Participants are strongly encouraged to bring in their own data sets and computers for practical work.

Software

Participants should have the following cross-platform software pre-installed.

R – v3.5 or later
RStudio Desktop – v1.1 or later