Class Statistics I

This course aims to provide students with an understanding of the fundamental principles underlying thought, language, and statistical methods. Throughout the learning process, students will be encouraged to recognize the relevance and broad applicability of these approaches across different fields, with particular emphasis on their respective areas of study.   The course also seeks to develop students' skills in data analysis and interpretation, while providing them with essential knowledge of probability theory and random variables. In addition, it promotes critical thinking and reasoning skills, enabling students to address and solve practical problems both within their academic fields and in a variety of other contexts.

Not applicable

1. Exploratory Data Analysis Introduction (sample, population) One-dimensional analysis: Data types. Frequency distribution and its graphical representation. Location measurements (average, median, mode, quantiles) Dispersion measures (sample amplitude, interquartile dispersion, variance, standard deviation, coefficient of variation) Two-dimensional analysis Scatter diagram. Coefficient of linear correlation Simple linear regression. 2. Probability Algebra of events and properties. Probability Concepts Kolmogorov's Axiomatic and its consequences Conditioned probability. Independent events Total probability theorem and Bayes theorem. 3. Random variables One-dimensional random variables Functions of a random variable Parameters (location and dispersion)

As part of the teaching and learning process for this course, innovative teaching strategies will be adopted to promote interactivity, active student participation, and the effective use of technological tools. In this context, the Moodle platform will play a central role, being used both to provide supplementary materials and learning resources and to support quizzes, short tests, and other learning activities.   The platform will also enable the monitoring of resource use and student progress, thereby contributing to a more individualized approach and strengthening formative assessment. The integration of digital activities will help consolidate the content covered in class, encourage student autonomy, and foster more dynamic participation. In this way, the course aims to implement a more innovative and interactive teaching model aligned with current educational needs.

Reis, E. (2019) Estatística descritiva, 7ª edição. Edições Sílabo Negas, E., Carreira, A. (2021) Estatística Descritiva - Explicação Teórica, Casos de Aplicações e Exercícios Resolvidos, 2º Edição. Edições Sílabo Murteira, B., Ribeiro,C.S., Silva, J.A., Pimenta, F. & Pimenta, C. (2015) Introdução à Estatística. Escolar editora