PREPARATORY COURSE - LABORATORY OF QUANTITATIVE METHODS

The pre-course aims to provide students with a common starting point from which to approach first-year courses that require basic quantitative skills with greater awareness and confidence.

The course is designed to consolidate and harmonize the knowledge needed to understand, interpret, and use numerical information and data. Taking into account the possible heterogeneity of students’ incoming backgrounds, the pre-course offers a guided review of the main tools of descriptive statistics, with particular attention to data reading, their synthetic representation, and the interpretation of results.

The course will have both a theoretical and an applied approach: alongside the review of fundamental concepts, students will engage in practical computer-based activities, using their own devices and dedicated software for data analysis and representation. This approach will enable students to translate statistical tools into concrete operations, making learning more practical and closely aligned with the needs of subsequent courses.

Attendance is strongly recommended for all students who wish to strengthen or harmonize their initial quantitative preparation.

At the end of the pre-course, students are expected to have acquired the basic quantitative knowledge needed to understand and develop simple data analyses using appropriate statistical software.

In particular, students are expected to have acquired the following.

1. Knowledge and understanding
- Know the terminology and fundamental concepts of descriptive statistics.
- Understand the role of data and quantitative information in the analysis of real-world phenomena.
- Recognize the main types of data and the most appropriate ways to summarize and represent them.
2. Ability to apply knowledge and understanding
- Be able to organize and describe simple datasets.
- Be able to choose the most appropriate tools for descriptive analysis, such as tables, graphs, and summary indicators.
- Be able to calculate and interpret measures of central tendency, variability, and association.
- Be able to read and understand simple quantitative results.
3. Making judgments
- Be able to critically assess the appropriateness of the descriptive tools used in relation to the type of data available.
- Be able to correctly interpret the results obtained, recognizing their limitations and conditions of validity.
- Be able to distinguish between data description and interpretations that are not supported by the available evidence.
4. Learning skills
- Be able to use teaching materials and reference texts to independently consolidate basic quantitative knowledge.
- Be able to identify any gaps in one’s initial preparation and develop strategies to address them.
- Be able to critically consult online resources and introductory materials in the field of descriptive statistics and data analysis.

Students are expected to be familiar with the basic mathematics normally covered in upper secondary school, as well as with the use of a computer.

The pre-course is designed for students with diverse educational backgrounds and does not require advanced preparation in statistics. The proposed activities aim to build a common level of initial quantitative skills, enabling students to approach more effectively first-year courses that involve the use of data, indicators, and quantitative reasoning.

During the pre-course the following descriptive statistics topics will be reviewed:

1. Introduction
2. Types of Data
3. Frequency Distributions
4. Graphical Representation
5. Measures of Centrality
6. Measures of Variability
7. Measures of Association

Chapters 1-2 of the book: Illowsky, D., Dean, S. (2022) Introductory Statistics, OpenStax (available for free download at https://openstax.org/details/books/introductory-statistics?Book%20details ).

The precourse does not include a final exam, nor are there any other forms of assessment of learning.

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The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

The precourse does not include a final exam, nor are there any other forms of assessment of learning.

Lessons with discussion and illustration of the methods presented through examples