Preface This book was born from the conviction that data analysis should be rigorous, accessible, and useful to all those who seek to understand reality through empirical evidence. We live in an era in which information is being produced at an unprecedented pace. In the Social and Health Sciences, researchers, students, and professionals are confronted daily with the need to collect, analyse, interpret, and communicate data in a sound and meaningful way. In this context, the ability to use appropriate data analysis tools is a fundamental competence for producing scientific knowledge and supporting informed decision-making. This work was conceived precisely with that purpose: to bridge theory and practice and to support the development of these competencies through a clear, progressive, and applied approach. The book is organised into twelve chapters, structured progressively so that readers can consolidate their knowledge from fundamental concepts to more advanced data analysis techniques. The journey begins with descriptive analysis, essential for exploring and understanding data, and continues through the main methods of statistical inference, including parametric and non-parametric tests, ANOVA, ANCOVA, and MANOVA. In a second stage, the book addresses methodologies dedicated to the analysis of qualitative variables, including tests of association, contingency table models, concordance analysis, measures of preference and consistency, as well as logistic regression models for binary, multinomial, and ordinal outcomes. The book then proceeds to modelling and multivariate techniques widely used in the Social and Health Sciences, including simple and multiple linear regression, exploratory factor analysis, cluster analysis, correspondence analysis, and decision trees. These methodologies enable readers to identify patterns, understand complex relationships among variables, and develop predictive models suitable for diverse research and professional contexts. The internal organisation of the chapters follows a pedagogical structure designed to facilitate progressive learning. Each chapter begins with a conceptual framework that helps readers visualise the main topics and the relationships among them. This is followed by the theoretical foundations required to understand the methods presented, combining scientific rigour with an accessible and practical approach. After the theoretical component, examples and solved exercises illustrate the application of the concepts in real situations drawn from the Social and Health Sciences. One of the distinctive features of this book is that each exercise is developed using four different analytical environments: IBM SPSS, JASP, Jamovi, and Python. This allows readers to compare procedures, understand the specific characteristics of each environment, and choose the tool that best suits their objectives. Such an approach promotes flexible learning and facilitates adaptation to a variety of academic, professional, and scientific settings. For Python users, all materials will be available in both Portuguese and English, contributing to the internationalisation of the project and enabling its use in both national and international academic contexts. Complementing the methodological chapters, Chapter 0 provides the resources required to make full use of the book, including guidance on installation, access, and use of the software employed throughout the text, together with information regarding the supplementary materials made available by the publisher. Readers therefore benefit from an integrated learning environment that combines theoretical foundations, practical exercises, and the use of contemporary analytical tools. During the development of this work, the authors also used Microsoft Copilot as a tool to support methodological reflection, content organisation, technical review, and the exploration of pedagogical strategies. The contribution of these emerging technologies highlights the potential of artificial intelligence as a complementary instrument for learning and scientific production. Nevertheless, full scientific, academic, and pedagogical responsibility for all content presented remains with the authors. This book also has a social and charitable dimension. We believe that knowledge achieves its deepest meaning when it is placed in the service of the community and of those who are most in need. With this spirit in mind, the project seeks to combine the promotion of scientific and statistical literacy with a social cause, dedicating all revenues generated by this edition to Lar Madre Teresa de Saldanha, an institution devoted to supporting young people in situations of social vulnerability. We hope that each copy acquired may transform knowledge into opportunity, learning into hope, and solidarity into action, allowing every reader to participate in a meaningful gesture of support towards those who need it most. To all students, teachers, researchers, and professionals who use this book, we hope it will serve as a valuable tool for learning, intellectual growth, and service to the community. Science is built through dialogue, the sharing of experiences, and the discussion of ideas. For this reason, the authors welcome suggestions, corrections, comments, and accounts of how the book has been used. Readers who wish to do so may contact the authors at: pestanapinagageiro@gmail.com Through the publisher’s online platform, readers will have access to the datasets used throughout the book, as well as solutions to the exercises in IBM SPSS, JASP, and Jamovi, together with Python notebooks containing the corresponding code, results, and interpretations. There is, however, a deeper conviction that the authors wish to share. Throughout history, different cultures and traditions have sought to understand the ultimate origin of knowledge, creativity, and existence itself. Some call it God, others Buddha, Creator, Supreme Intelligence, Universal Love, or use other names to express their understanding of what transcends the human condition. The authors deeply respect all such perspectives and recognise the freedom of each individual to follow their own path. For their part, the authors believe that the ability to learn, teach, investigate, create, and share knowledge is not an exclusively individual achievement. They regard it as a gift received, together with all that they are and all that they possess, and therefore seek to place this gift in the service of others. Just as blind trials in scientific research evaluate the quality of a product independently of its source, we hope that this book will be judged above all by the value it may provide to its readers rather than by the academic titles, positions, or curricula of its authors. More important than the names and titles appearing on the cover are the usefulness of the knowledge shared, the rigour of the methods presented, and the book’s ability to contribute to learning, research, and the improvement of people’s quality of life. For that reason, and for academic and editorial purposes, only the names of the authors have been included in the work. Finally, we leave a heartfelt word of gratitude to the Higher Being who inspires this work and who, often in ways unseen, continues to illuminate the path of those who seek to learn, teach, investigate, and serve others.

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