Proponent: Davide Gentilini
Course learning outcomes/abstract: Data management and analysis is one of the most important and most critical factors in many work areas; proprietary tools and software are often expensive or limited in their application. R can be defined as an environment for statistical analysis and at the same time a language and a software. It is a very powerful and widely used open source tool for statistical analysis of data, moreover, being a real programming language, it contains the potential to independently create and develop various applications useful for manipulation, management and analysis of any type of data. In fact, its main features include simplicity in data management and manipulation, the availability of a suite of tools for calculations on vectors, matrices and other complex operations, access to a vast set of integrated tools and functions developed by others and made available for statistical analysis, the production of numerous particularly flexible graphic potentials, the possibility of using a real object-oriented programming language that allows the use of conditional and cyclic structures, as well as functions created by the user. Offering an elaborate introduction to programming with R, this course aims to intercept the needs of the participants by focusing in particular on some fundamental aspects such as data manipulation and management, their analysis through the identification of the most appropriate statistical test and the visualization of data and results using the graphic potential made available by R.
The course involves the use of numerous “datasets” and examples that may be familiar to the various areas of interest in order to facilitate participants in understanding and applying the knowledge acquired.
Goals: The course aims to provide participants with the necessary and sufficient knowledge to introduce and use the language and potential of R in their work.
Number of hours and planning: The course will last at least 20 hours (5 CFU), and will be divided into 5 meetings
Period: The course period will be from 11 to 15 September 2023 (summeR school) The calendar may be subject to change
PhD courses involved: The course aims to be transversal and to provide useful skills in every area that has to do with data and the need to process and manage them. For this reason, the course aims to be useful to any type of doctorate, in particular the macro-area of Life Sciences.
Delivery mode and location ( in presence, on line, ecc): in presence
Evaluation criterial: The degree of learning will be tested at the end of each lesson by subjecting the participants to a test. The test will consist of a series of 10 multiple choice questions regarding the theoretical part to which an exercise relating to the topics covered will be added.
Credits (CFU): 5