Curricular Unit:			Code:
Statistics and Quantitative Methods in Management			1175EMQG
Year:	Level:	Course:	Credits:
1	Undergraduate	Business Sciences	6 ects
Learning Period:		Language of Instruction:	Total Hours:
Spring Semester		Portuguese/English	78
Learning Outcomes of the Curricular Unit:
This course aims to introduce statistical analysis techniques in a scientific approach. In particular, the course focuses on understanding the importance of statistical methods, on the ability to apply them and on developing a critical and analytical judgment of data, as well as its synthesis leading to decision making in situations of uncertainty, present in many areas in the field of Business Sciences. In this context, students will be able to: - Calculate statistics and distinguish them from parameters; - Characterize a set of data (sample or population) and make correct interpretations; - Identify associations between variables that can support basic relationships for forecasting models. - Identify and use specific models of probability distributions; - Use statistical inference tools: confidence intervals and hypothesis tests.
Syllabus:
1. Basic statistical concepts 2. Descriptive Statistics 3. Association between two variables 4. Probabilities and random variables 5. Confidence intervals estimate 6. Parametric hypothesis tests 7. Multiple linear regression model
Demonstration of the Syllabus Coherence with the Curricular Unit's Objectives:
Sections 1-3 are related to objectives: Ability to calculate statistics and distinguish them from parameters; Ability to properly characterize the data set (sample or population) and make their correct interpretation. Sections 4-7 are related to objectives: Ability to identify and use specific models of probability distributions; Ability to use statistical inference tools: confidence intervals and hypothesis testing.
Teaching Methodologies (Including Evaluation):
This course uses an expository, descriptive and demonstrative methodology within the scope of theoretical-practical classes, resorting to the resolution of practical situations that allow the application of the syllabus contents. Knowledge assessment is carried out continuously, with two tests weighing 50% each. Test # 1 evaluates sections 1 to 3, and Test # 2 evaluates sections 4 to 7.
Demonstration of the Coherence between the Teaching Methodologies and the Learning Outcomes:
Given the essentially practical nature of that course all exposed concepts are applied to the resource to solve a number of exercises. This methodology allows to achieve the specific goals listed in each section of the syllabus.
Reading:
Fernando, M. (2009). Statistics for Business and Economics. Ventus Publishing. Guimarães, R. e Sarsfield Cabral, J. (1997). Estatística. McGraw-Hill. Jonsson, R. (2014). Exercises in Statistical Inference. 1ª Edição. Ventus Publishing. Keller, G. (2005). Statistics for Management and Economics. Thomson. Reis, E. (2008). Estatística Descritiva, 7.ª Ed. Edições Sílabo. Reis, E.; Melo, P; Andrade, R e Calapez, T. (2021). Estatística Aplicada – vol. 1, 7.ª Ed. Edições Sílabo. Reis, E.; Melo, P; Andrade, R e Calapez, T. (2019). Estatística Aplicada – vol. 2, 6.ª Ed. Edições Sílabo. Reis, E.; Melo, P; Andrade, R e Calapez, T. (2021). Exercícios de Estatística Aplicada – vol. 1, 3.ª Ed. Edições Sílabo. Reis, E.; Melo, P; Andrade, R e Calapez, T. (2021). Exercícios de Estatística Aplicada – vol. 2, 3.ª Ed. Edições Sílabo.
Lecturer (* Responsible):
Fátima Rocha (frocha@ufp.edu.pt) Sandra Bernardo (sbern@ufp.edu.pt)