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. In the theoretical part of the lesson, the interactive expository method will be frequently used to introduce concepts, fundamental results, and methods, in order to encourage active participation by all students. The practical part will be designed to problem-solving, with computer support, under the guidance of the teacher. The two parts will be interspersed in a sequence that optimizes the acquisition of skills.
Support materials are available on the Nonio platform.
Learning Results
This curricular unit aims to provide students with knowledge in the field of univariate, bivariate and multivariate statistical techniques for data analysis.
The student must be able to:
– perform univariate and multivariate exploratory analyses, using statistical software.
– select and apply different statistical techniques, in order to obtain results that support decision making in uncertain environments.
Program
1. Statistical Notes
1.1 Review of basic statistical concepts
1.2 Parametric and nonparametric hypothesis testing
2. Multivariate Statistics
2.1 Factor analysis
2.2 Regression analysis
Curricular Unit Teachers
Maria Manuela Coelho LarguinhoGrading Methods
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.
Internship(s)
NAO
Bibliography
Main Bibliography
Maroco, J. (2021). Análise Estatística com o SPSS Statistics. 8ª Edição, ReportNumber.
Alwan, L. C., Craig, B. A. and McCabe, G.P. (2020). The Practice of Statistics for Business and Economics, 5th Edition. Macmillan Learning.
Newbold, P., Carlson, W. and Thorne, B. (2019). Statistics for Business and Economics, 9th Edition. Pearson.
Complementary Bibliography
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2019). Multivariate Data Analysis, 8th Edition. Cengage.
Anderson, D.R., Sweeney, D.J. and Williams, T.A. (2000). Estatística Aplicada à Administração e Economia. Pioneira
Maroco, J. (2014). Análise de Equações Estruturais – Fundamentos teóricos, Software e Aplicações. Report Number
Hill, M., Hill. A. (2012). Investigação por questionário, 2.ª edição revista e corrigida. Edições Sílabo.