Statistical Methods

Base Knowledge

Preliminary data analysis and graphical representation.

Teaching Methodologies

In order to achieve the objectives of the curricular unit and conference of the competencies provided to the student, the learning process is based on the study of cases, accompanied by a set of instructions and statistical/computer tools that lead the student to analyze each case and draw conclusions; in the execution of practical work of applying theoretical concepts; in the bibliographic research necessary to complement the information obtained in the classes.

Learning Results

1) Identify quantitative/qualitative data.

2) Select appropriate statistical analysis techniques to describe the data.

3) Numerically and graphically organize the results of the use of different statistical methodologies.

4) Correctly interpret numerical and graphic results.

5) Use data analysis programs (Microsoft Excel / SPSS – Statistical Package for Social Sciences).

Program

Module 1 (50%):

1. Descriptive statistics.

2. Elementary probability theory. Discrete and continuous one-dimensional random variables. Most common theoretical distributions: discrete and continuous.

3. Confidence interval and hypothesis tests for a population parameter.

Module 2 (50%):

4. Analysis of variance. Nonparametric tests.

5. Simple linear regression.

Grading Methods

Continuous assessment:

Presence, at least, in 75% of the classes effectively taught - Regulamento de Avaliação do Aproveitamento dos Estudantes (RAAE) da ESAC

Module 1 (M1) - Evaluates the learning outcomes of chapters 1, 2 and 3. Weight: 50%.

  • Written test 1 (T1) - 35%
  • Group Work 1 (TG1) - 15%


Module 2 (M2) - Evaluates the learning outcomes of chapters 4 and 5. Weight: 50%.

  • Written test 2 (T2) - 35%
  • Group Work 2 (TG2) - 15%

Tests and group work are mandatory. Minimum grade per module of 7.5 values. 

Final grade = 0.50 *M1 + 0.50 * M2

To obtain approval, in continuous evaluation, the student has to meet the minimum attendance required by the RAAE and the final grade resulting from the weighted final grade equal to or greater than 9.5 values (scale 0-20).

Assessment by exam:

Exam to assess both modules.

If the student, in the continuous assessment, has obtained a minimum grade of 7.5 in one of the modules, he/she can reuse the grade for that module. When performing proof for only one of the modules, the minimum grade of 7.5 values is maintained. Approval in the curricular unit depends on obtaining a minimum of 9.5 values in the final grade.

In the exam for grade improvement, there is no place for the reuse of grades obtained in continuous evaluation.


    Internship(s)

    NAO

    Bibliography

    Murteira, B., Ribeiro, C., Silva, J., & Pimenta, F. (2015). Introdução à Estatística. Escolar Editora.

    Levine, D., Stephan, D. & Szabat, K. (2016). Estatística: Teoria e Aplicações usando o Microsoft Excel em Português. LTC Editora.

    Pestana, M. H. & Gageiro, J. (2014). Análise de Dados para Ciências Sociais: A complementaridade do SPSS. Edições Sílabo.

    Hall, A., Neves, C. & Pereira, A. (2011). Grande Maratona de Estatística no SPSS. Escolar Editora.

    Maroco, J. & Bispo, R. (2005). Estatística aplicada às ciências sociais e humanas. Climepsi Editores.