Applied Statistics for Research

The classes are designed, according to the curriculum plan, to be both theoretical and practical. They are planned and prepared
considering active learning activities, to actively engage all students at various moments or throughout the entire class.
In the theoretical part of the lesson, the expository method will be frequently used to introduce concepts, fundamental results, and methods,
interspersed with tasks that encourage active participation by all students. These tasks include posing questions to and by students, orally,
as well as proposing debates/discussions in small groups on certain exposed aspects/topics.
The practical part will be designed to comprehensively develop the listed skills. This will be achieved through problem-solving, using
software, under the guidance of the teacher. Autonomous work or work in small groups will be encouraged. There will be a strong
interaction between theory and practice, with a central focus on visualizing and dealing with actual scenarios.

This course focuses on essential methodological aspects for empirical research in Accounting and Taxation, from the initial data collection
phase to advanced statistical analysis and interpretation of results.
The following learning outcomes are therefore defined:
1. analyze the use of statistics in scientific literature in the area of business sciences;
1. plan the stages of the empirical research process, including selecting the most appropriate data collection methods to fulfil the research
objectives;
2. identify the most appropriate statistical techniques taking into account the research objectives;
3. carry out statistical analyses using software, extracting the relevant and essential information from the output;
4. interpret the results of the statistical analysis, identifying the extent to which they enable the research questions to be answered/clarified.

1. The empirical research process
1.1. Introduction
1.2. Data collection: sampling and questionnaires
2. Statistical data analysis
2.1. Univariate and bivariate statistical techniques: an overview
2.2. Multivariate statistical techniques

NAO