OVERVIEW

Data analysis and extraction of useful information contained in data is assuming a growing interest in the scientific field and beyond. In fact, there is an ever-increasing capacity to collect and store data, and it is therefore essential to know how to manage and process them in order to obtain reliable results. Also of fundamental interest is their effective and immediate representation to maximize the understanding of the phenomenon under investigation.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to provide tools for processing data from the laboratory or from the most modern practices implemented in service pharmacy and hospital pharmacy. These tools include both the theoretical basis of statistical tests and their practical implementation through the use of spreadsheets and dedicated software. Particular attention will be paid to the graphical representation of the data and to their interpretation. The course includes practical computer exercises in order to make the student autonomous in the extraction of useful information from chemical and other type of data. The skills acquired after this course will be fundamental during the degree program and in future professional tasks, especially in the context of laboratory activities.

AIMS AND LEARNING OUTCOMES

At the end of the course the student will be able to:

• Define the concepts of location, dispersion and the descriptive parameters for a probability distribution.
• Use the basic functions of the MS-Excel software
• Knowing how to correctly and effectively represent the results obtained from data processing

PREREQUISITES

There are no prerequisites for this course

TEACHING METHODS

50% of the lessons of the course is composed by frontal lessons: the teacher, with the help of multimedia presentations and demonstrations using software, will illustrate the contents of the course.

The remaining 50% of the course will be carried out in accordance with the most innovative participatory teaching strategies, in order to stimulate student learning. In particular, it is foreseen to carry out exercises in the classroom and to assign exercises as homework through the use of software.

The last two lessons of the course will be dedicated to the correction of the assigned exercises, as well as to the execution of exam simulations for improving self-assessment.

Depending on the University provisions, the teaching activity can be carried out remotely with the help of MS-Teams. The course program and teaching methods will not change.

SYLLABUS/CONTENT

Applications of statistics in analytical chemistry.

Basics of descriptive statistics. Random, population and sample experiments. Absolute and relative frequency. Location and dispersion: descriptive parameters of a probability distribution.

Use of spreadsheets and representation of results.

Basic functions for spreadsheets: conditional functions, string extraction and concatenation, pivot tables. Bar, pie and scatter plots; pivot charts.

RECOMMENDED READING/BIBLIOGRAPHY

Although the slides provided by the teacher (and downloadable in .pdf format from the course website on the AulaWeb platform) contains much of the information necessary for studying the subject and passing the exam, the following text is recommended:

Chimica Analitica
L. Sabbatini, C. Malitesta, P. Pastore
Format: flexible cover
Edition: EdiSES (I/2025)
N. Pages: 820
ISBN: 9788836231942

The text is useful for all analytical chemistry subject courses: Analisi dei Dati mediante Strumenti Informatici, Chimica Analitica, Analisi dei Medicinali I, Analisi dei Medicinali II, Analisi Strumentale dei Farmaci. The contents of this course are presented in Chapter 1.

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

Classes will start in accordance with the academic calendar. Any changes to the timetable will be communicated on the course dashboard on the AulaWeb platform.

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists of a written test with multiple choice questions.

Each student will be asked 20 questions presented in random order and different for each candidate (the test texts are generated by the teacher using software, in order to produce diversified exercises, but of comparable complexity, for each of the students enrolled). The questions will be divided as follows: 10 relating to the understanding and learning of the basic concepts of statistics, 5 which involve carrying out exercises on the MS-Excel spreadsheet (duly indicated in the text of the exam as "star exercises"), 5 relating to the graphical representation of the results obtained from data processing.

The written test is considered passed if at least 12 questions are answered correctly, of which at least 2 must be related to exercises involving the use of MS-Excel (duly indicated in the text of the exam as "star exercises"). The time available is one hour.

In order to take part in the written exam, it is mandatory to register through the student portal.

The outcome of the written exam will be communicated by the teacher publishing a news on the course dashboard in the AulaWeb platform.

Depending on the current situation and the University provisions, the exam can be carried out remotely, without any change in the modalities, via the MS-Teams telematic platform, in a dedicated channel which will be communicated to the candidates in the days immediately preceding the carrying out the written test. To allow the teachers to monitor the progress of the tests, the candidate must keep the microphone and webcam active for the entire duration of the exam.

ASSESSMENT METHODS

The written exam will allow to verify the knowledge acquired by the student both from a conceptual and procedural point of view, thanks to the carrying out of numerical exercises, of content and complexity comparable to those carried out in the classroom. For the purposes of the evaluation, only the accuracy of the final result presented for each exercise will be considered by choosing the correct answer from those available in the question.

FURTHER INFORMATION

For any updates that may become necessary during the academic year, students are referred to the course dashboard on the AulaWeb platform.

For students with DSA, disability or other special educational needs certification, it is requested to contact the teachers at the beginning of the course to agree on teaching and exam methods which, in compliance with the teaching objectives, take into account the methods learning opportunities and provide suitable compensatory tools.