MoBi Bachelor – Data Analysis – WS 2022/2023

Teachers

• Carl Herrmann (carl.herrmann (at) bioquant.uni-heidelberg.de)
• Maiwen Caudron-Herger (m.caudron (at) dkfz-heidelberg.de )

Content

The purpose of this course is an introduction to basic techniques of scientific data analysis, which every scientist will be confronted with. It combines concepts of good practice in data analysis, statistical concepts, and practical implementation in R.

We will cover:

• data visualization (plots)
• descriptive statistics (mean, variance, correlation,…)
• data exploration and reduction (PCA, clustering,…)
• inference statistics (P-values, tests,…)
• data modelling (linear/logistic regression,…)

Each lecture (Thursday) will be followed by a practical session (Friday) under R/RStudio

Reference

Books

• Intuitive Biostatistics by Harvey Motulsky (Oxford University Press)
• Discovering statistics using R by A. Field, J. Miles, Z. Field (SAGE publications)

Websites

This class is supported by DataCamp, an intuitive learning platform for data science and analytics.

• DataCamp free online R introductory course
• R for the data science
• Data Analysis for the Life Science

Practical information

• Online discussion on Thursday (11h15 - 13h) discussing the content of the online recorded lecture
• Hands-on exercises on Friday (10h - 11h30 and 12h-13h30) (IPMB, 5th floor, CIP Room)

Learning R will also be supported using online courses by Data Camp.

Recorded Lecture and slides

Will be put online every week

• Week 1: exploratory analysis, plots,…
  • Part 1: data types
  • Part 2: Plotting data
  • Part 3: Mean, median, spread
  • Part 4: Quantiles, QQ-plots

Link to practical parts

Will be put online every week