1. R4BS Infobiology course
In questa sezione conosciamo "R" e il concetto (comune nella statistica) di "tidy data".
3. Using R for the first time
In questa sessione installiamo "R" e "RStudio" sul nostro computer e ne impariamo l'utilizzo di base.
4. Practice and again practice
In questa sessione facciamo un po' di pratica (esercizi).
Materiali corso (download)
Aim of the R4BS course
Aim of R4BS (R for Biological Statistics)
[Obiettivi di “Statistica pratica per biologi con R”]
If you’re here is because you want learn statistic, and maybe you want to do it in an “R” way, it’s because you feel that it is relevant for your profession. This is very true for the life science professions: statistics is key, and R is becoming more and more relevant for biologists, technicians and clinicians, and probably you’re one of them.
This is a course of “Practical” Statistics, so you need to learn both R programming basic concepts and Statistical concepts. The R4BS course is designed to teach you statistical reasoning through the R-driven exploration of data, which is the approach currently adopted by biological data scientists and reasearchers.
The R scripting concepts are kept at a minimum, just what you need to approach the statistical concepts. The online lessons on this platform will be entirely dedicated to what “R” is, how does it work and how you can work with it. The first live day in the classroom we will spend a substantial fraction of time refraining these concepts too. You can easily follow this course even if you do not have any informatics experience, but be prepared to face a different paradigm of approaching data: this can be a little challing at first but it’s definitely doable for anyone with a degree-level of instruction, and it will bring huge advantages.
So let’s clarify an important thing form the beginning: this course is just the first step of your commitment!
Of course, you will need more time than just a couple of days to fully master the concepts and the use of R (well, we have another course for this…). You will also need to reserve time in your daily routine to reason on the statistical concepts, trying to look at your data in a different way. Maybe in a non-distant future you’ll want to dive deeper into more complex methods such as machine learning or R programming; this is very doable if you will follow some rules and you will accept to be lead by those who already traveled this road.