Applied Statistics for Research

Base Knowledge

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

Teaching Methodologies

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.

Learning Results

Statistics is a science of recognized importance, with applications in various scientific fields, including business sciences. This course unit 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.

Thus, the following learning objectives and competencies are defined:

  • Critically analyze the use of statistics in the scientific literature in business sciences;
  • Plan and structure the different phases of the empirical research process, including selecting the most appropriate data collection methods to fulfil the research objectives and questions;
  • Identify and apply the most appropriate statistical techniques taking into account the research objectives and questions;
  • Carry out statistical analyses using statistical software, extracting the relevant and essential information from the corresponding outputs;
  • Interpret, evaluate, present, and communicate the results of the statistical analysis, identifying the extent to which they enable the research objectives and questions to be answered or clarified

Program

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

Curricular Unit Teachers

Barbara Alexandre Regadas Correia Baía

Grading Methods

In this course unit, students are assessed under a periodic assessment regime, which includes two mandatory components: coursework and a written exam. Therefore, assessment based solely on an exam is not permitted.

 Coursework

  • The coursework is graded on a scale from 0 to 10, and the coursework guidelines are made available on the InforEstudante|Nonio platform.
  • The coursework consists of the coursework components (file(s) generated using the software, a written report, and a presentation), to be submitted by the deadline specified on the InforEstudante|Nonio platform, accounting for 70% of the grade for this component, as well as an in-person presentation and discussion, conducted during the scheduled period, accounting for 30% of the grade for this component.
  • Completion of the coursework is mandatory in all assessment periods. However, its format, as well as the deadlines for submission, presentation, and discussion, vary according to the assessment period:

           a) When completed during the regular examination period, the coursework is carried out in groups of 2 to 4 students, with the deadline for submission of the coursework components being the end of the Monday preceding the final class of the term. The presentation and discussion take place during the final class of the term, and participation by all group members is mandatory.

           b) When completed during the resit or special examination period, the coursework is completed individually, with the deadline for submission of the coursework components being the end of the fourth business day prior to the date of the exam for which the student is registered. The presentation and discussion take place on the exam date.

Examination

  • The exam consists of an individual written test, open-book, graded on a scale from 0 to 10, and administered on the date specified in the exam schedule.
  • The exam includes questions assessing both the theoretical and practical components of all topics covered in the course. Some questions include outputs generated by the statistical software used, which requires proper interpretation.

 

Final Mark:

The final mark (CF) is calculated using the following formula, with the result rounded to the nearest whole number:

CF = CT + CE

where:

- CT is the mark obtained for the coursework, on a scale from 0 to 10, without rounding;

- CE is the mark obtained on the written exam, on a scale from 0 to 10, without rounding.

Students who earn a final grade of at least 10 are considered to have passed the course unit.

 

Notes:

  • The grade obtained for the coursework completed during the regular assessment period remains valid for the resit and special assessment periods.
  • For grade improvement purposes, students may choose one of the following options:

           a) take a new exam in the assessment period in which they are registered for grade improvement, while retaining the group coursework grade;

           b) take a new exam and complete new individual coursework, both in the assessment period in which the student is registered for grade improvement.


    Internship(s)

    NAO

    Bibliography

    Alwan, L.C., Craig, B.A., & McCabe, G.P. (2020). The Practice of Statistics for Business and Economics, 5th Edition. MacMilan.
    Coutinho, C.P. (2018). Metodologia de Investigação em Ciências Sociais e Humanas: teoria e prática. 2.ª Edição. Almedina.
    Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. (2019). Multivariate Data Analysis, 8th Edition. Cengage.
    Marôco, J. (2021). Análise Estatística com o SPSS Statistics, 8.ª Edição. ReportNumber.
    Pestana, M.H. & Gageiro, J.N. (2014). Análise de dados para ciências sociais: a complementaridade do SPSS, 6.ª Edição. Sílabo
    Saunders, M.N.K., Lewis, P. & Thornhill, A. (2019). Research Methods for Business Students, 8th Edition. Pearson.