Coding and Data Crunching

Full course description

This course teaches the basics of scripting, data analysis and statistics. Statistical tools for modern data analysis are used across a range of industries to help guide organisational, societal and scientific advances. This course uses the software package R for numerical reasoning and predictive data modelling, with an emphasis on conceptual rather than theoretical understanding. Topics include description of populations, distribution of data, inferential statistics (based on simple tests such as t- and chi-square tests), introduction to linear regression analysis and concept of probability (including Bayes’ rule, disjoint and independent events (multiplicative rules), law of total probability). These will be introduced in cases related to regenerative medicine. 

To apply the theoretical statistics concepts, students will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in scripting. The cases used in the programming activities will be related to regenerative medicine.  This course is envisioned as an introduction to scripting; its goal is that students learn how to handle data sets and to automate the analysis thereof using a programming language. The students will learn to plan and think carefully about why a particular analysis is needed, what should be done etc. before starting to write the script. Topics include basic control structures, graphical data presentation, biomedical data handling (including legal and ethical aspects thereof). Additionally, this course will contribute highly to the personal development line of the students with focus on problem solving.