Intended learning outcomes (knowledge, skills and competences to be developed by the students):

Development of the autonomous ability to use statistics, as well as data analysis tools, with a particular focus on the biomedical context. It is
intended, with this Curricular Unit, to ensure the independence of students in the field of scientific research, in terms of: i) formulation of
hypotheses and scientific questions in a statistically coherent and consistent way; (ii) design of the studies necessary to obtain the
respective answers; iii) execution of these studies, knowing how to treat and analyze the data; iv) understanding of the limitations of the
tools used, having the critical ability to analyze data from various perspectives; v) ability to analyze results and draw statistically relevant
and valid conclusions; and vi) knowledge of scientific writing of statistical methods and results, as well as their understanding and analysis.

Syllabus:

Module 1: Introduction:

• Qualitative analysis and scientific thinking;
• Variables and scientific questions;
• Sampling;
• Data visualization;
• Basic descriptive statistics;
• Introduction to IBM-SPSS.

Module 2: Data Exploration and Basic Inference:

• Exploratory data analysis;
• Basic distributions;
• Parameters and estimation;
• Confidence intervals;
• Hypothesis testing;
• Normality tests;
• Parametric vs non-parametric tests;

Module 3: Inferential Statistics and Diagnostic Tests:

• Risk analyses;
• Diagnostic tests and ROC curves;
• Reliability and validity;
• Linear regression;
• Effects and errors;
• ANOVA