Statistics Applied to Information Systems

This curricular unit requires a basic knowledge of statistics, corresponding to the Statistics curricular unit(s) of an undergraduate degree.

Theoretical-practical classes, as stipulated in the curriculum.

• Theoretical component: exposition of concepts and resolution of illustrative examples; questions to the students during the presentation.
• Practical component: resolution of illustrative and complementary practical exercises of the material exposed in theoretical classes, under the guidance of the teacher, but encouraging autonomous resolution (using statistical software).

Statistics is a science of recognised importance, with applications in various scientific domains, including the field of information systems, and also providing the foundations for numerous machine learning approaches. Thus, this course aims to introduce a set of statistical techniques for processing, analyzing, and interpreting data within the context of information systems, using statistical software.

The following learning outcomes are therefore defined:

1. Plan the stages of the statistical method, specifically identifying the problem, processing the data, and selecting the most appropriate statistical techniques according to the defined objectives;
2. Carry out statistical analyses using software, extracting the relevant and essential information from the output;
3. Interpret the results of the statistical analysis, determining to what extent they address or clarify the established objectives.

Chapter 1 – Basic Concepts

• Statistics and Machine Learning
• Statistical techniques for descriptive data analysis
• Hypothesis Testing

Chapter 2 – Multivariate Statistics

• Factor analysis
• Clusters analysis

Chapter 3 – Econometric Models

• Regression models (linear)
• Extension of the regression models

NAO