Teaching Methodologies
The classes are designed, according to the curricular plan, to be both theoretical and practical. They are planned and prepared considering active learning activities, to actively engage all students at various moments throughout the entire class.
The Teaching and Learning Methodologies (TLM) integrate theory and practice to develop statistical skills:
TLM1. Lectures: In the theoretical part, introducing concepts, fundamental results, and statistical methods/techniques (OA1), the expository method will tend to be used interspersed with tasks that elicit active participation from all students. These tasks will include the asking of questions to and by the students, orally and also with the proposal of debate/discussion in small groups on some aspect/topic exposed.
The practical part will be aimed at the full development of the skills listed, through:
TLM2. Solving real problems: Application of statistical techniques in software, accompanied by the teacher (OA2), encouraging autonomous work or in small groups. A strong interaction between theory and practice will prevail, giving as much as possible a central role in the visualization and treatment of concrete and real situations.
TLM3. Group work: Analysis and interpretation of data, promoting critical thinking and autonomy (LO3).
Learning Results
Statistics is a science of recognized importance, with applications in various scientific fields (e.g. marketing, management, …). This course therefore aims to present a set of statistical techniques for analyzing and interpreting data, using statistical software.
Learning Objectives (LO)
LO1 Plan the phases of the statistical method, including problem identification, data processing, and the choice of statistical techniques
LO2 Apply statistical techniques using software, extracting and interpreting results
LO3 Interpret/evaluate statistical results, determining their contribution to objectives
Competences/Skills (C)
C1 Develop the ability to identify problems and select appropriate statistical techniques (LO1)
C2 Acquire practical skills to carry out statistical analysis and interpret outputs accurately (LO2)
C3 Demonstrate critical thinking in evaluating and communicating statistical results (OA3)
Program
1. Introduction to Statistics
1.1 Descriptive analysis
1.2 Estimation and Hypothesis Testing
2. Multivariate Statistics
2.1 Factor analysis
2.2 Clusters analysis
3. Econometric Models
3.1 Linear regression models
3.2 Extension of the regression models
Internship(s)
NAO
Bibliography
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2022). Multivariate Data Analysis (9th ed.). Cengage Learning
Maroco, J. (2021). Análise Estatística com o SPSS Statistics. 8ª Edição, ReportNumber.
Newbold, P., Carlson, W. & Thorne, B. (2022). Statistics for Business and Economics, Global Edition. Pearson.
Sarstedt, M., & Mooi, E. (2022). A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics (4th ed.). Springer.
Tintle, N., Chance, B.L., Cobb, G.W., Rossman, A.J., Roy, S., Swanson, T. & VanderStoep, J. (2020). Introduction to Statistical Investigations, 2nd Edition. Wiley.