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

In this curricular unit, the student, to be succeeded, will have to carry out two assignments and an exam, both mandatory components. Each assignment will be performed in groups (maximum of 4 students), and graded at 5 marks. The exam is a written test (10 marks), composed of questions containing statistical software outputs and covering all the chapters of the program.

The final classification is obtained by applying the following formula, the result of which is rounded to the nearest integer: CF = CT1 +CT2+CE, where CT1 and CT2 are the grades obtained in the 1st and 2nd assignments, respectively, on a scale of 0 to 5, without rounding; CE is the grade obtained in the written test, on a scale of 0 to 10, without rounding.

Students who obtain a minimum final classification of 10 will be approved.

Observations

1) The realisation of both assignments is compulsory at any exam season.

2) The classifications obtained in assignments are valid for all the exam seasons.

3) In other exam seasons, 2 assignments are also mandatory, and the deadline for the delivery is the day scheduled for the Exam. Students who opt for this modality will have to carry out the 2 assignments individually. The calculation of the final classification follows the rules stated above.

 4) To improve their grade, students can choose one of the following options:

     a) take a new exam, keeping the grades from the two group assignments;

     b) take a new exam and complete two new individual assignments, both in the same exam season in which the student is enrolled for grade improvement.

NAO