Ateneo - UPO

The R software and its use to represent data and for statistical data analysis.

Recommended Textbook: R for Data Science (https://r4ds.hadley.nz/). Additional reference material and course notes will be posted on the DIR website.

Knowledge and Understanding: The course aims to enrich the theoretical knowledge of statistics and probability by providing appropriate computational tools for data analysis, also demonstrating how to visualize the results. The chosen tool is the free and open-source R software.
Applying Knowledge and Understanding: Students are expected to be able to use the acquired knowledge even in multidisciplinary contexts, concretely analyzing data and creating professional graphical representations
Making Judgements: At the end of the course, students are expected to be able to apply the learned methods even in different situations and, if required, possess the tools to autonomously extend their knowledge..
Communication Skills: At the end of the course, students should acquire the ability to express the results of data analysis both numerically and graphically.
Learning Skills: During the course, students will acquire the ability to study and learn by choosing their personal path with originality, and they should be able to select the appropriate resources, potentially including online ones.
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Basic knowledge of mathematics and statistics

The course delivery method (traditional classroom or computer lab) will be determined based on the IT tools possessed by the students. The course will incorporate interactive lectures, live coding demonstrations, and hands-on practical exercises to facilitate direct application of R software.

Reference material and additional informations are posted on the DIR website.
Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities
Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can contact me to define the examination modalities, concerning academic aspects.

Assessment will be based on an online final examination. The tests will take place on DIR and consist of a series of exercises aimed at addressing issues covered during the course. The exercises are of various types and may range from simple theoretical questions to more complex ones requiring the download of datasets and their analysis. The ongoing tests will serve as preparation and an intermediate benchmark for the final exam.

R software. Elementary operations. Functions and graphs. Import, export in R. Data Structures, packages. Matrices, lists, arrays. The data frame. Working with data: selecting elements, logical operators. Loops and conditionals. Missing data. Additional graphics packages: ggplot2. Regression line and regression curves. Anova. Introduction to basic pharmacokinetic models. Introduction to clustering techniques (e.g., K-means) and their application in data analysis. Simulations. Text manipulation.

Upon completion of the course, students will be able to:
Utilize acquired knowledge in a multidisciplinary field to analyze data and create professional graphic representations.
Apply the learned methods even in different situations and possess the tools to extend their knowledge autonomously.
Express the results of a data analysis both numerically and graphically.
Study and learn by choosing their personal path with originality, and be able to select useful resources for their study, potentially including online ones.