Statistics

The course aims to provide students with the basic principles of descriptive statistics to enable them to independently carry out simple data analysis and to interpret tables, graphs and the summary indicators commonly reported in journals, periodicals and books.
The course will cover various types of data analysis by constructing frequency tables and their graphical representations. Teaching will also look at the main summary indicators (mean, mode and median) while also emphasising the importance of introducing other indicators in order for students to be able to interpret them.
The course will also deal with the detection and synthesis of two real phenomena (by means of contingency tables). Besides analysing each phenomenon separately, students will explore the dependence between both phenomena, since in many practical contexts (including the economic and legal context) it is important to be able to determine whether and to what extent a given phenomenon is dependent on another (e.g. for forecasting purposes).
Teaching will combine practical exercises with theory to enable students to acquire the necessary data analysis skills.

Upon completion of the course, students will understand the basic principles of descriptive statistics. More specifically, they will be able to summarise the information contained in a given data set through the use of frequency tables, graphs, and the appropriate indicators, and should be able to adequately interpret the summaries produced. Students will also be able to determine whether two real phenomena are dependent on one another and to provide future forecasts of a phenomenon of interest. This latter capability is fundamental at a practical level.
Similarly, students will understand the most common indicators reported in the media and will be able to accurately interpret information presented in tables and charts. These skills will enable students to give a more critical reading of commonly used statistical indicators and will allow them to make decisions with a greater sense of awareness.
By gaining an in-depth understanding of the concepts outlined during teaching and by performing exercises in data analysis, students will have the opportunity to acquire skills valuable for their further education and professional development.