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
The objective of this curricular unit is to promote, in the student who successfully completes it, the skills that are listed below.
As a result of the learning process, the student:
1) Understands statistical language and notation;
2) Addresses the main concepts and methods necessary for sumarization and interpretation of data;
3) Prepares and executes statistical tests and interprets the results;
4) Applies appropriate statistical techniques to support the decision-making process.
Program
Module 1 (60%):
1. Descriptive statistics.
2. Probability distributions. Discrete and continuous one-dimensional random variables. Common distributions: discrete and continuous.
3. Confidence interval and hypothesis tests for a parameter of a population.
Module 2 (40%):
4. Analysis of variance. Nonparametric tests.
5. Simple linear regression.
Curricular Unit Teachers
Cláudia Susana Pereira dos SantosGrading Methods
Continuous assessment:
Presence, at least, in 75% of the classes effectively taught - ESAC Student Achievement Assessment Regulation
Test 1 (T1) - Evaluates the learning outcomes of module 1 (chapters 1,2 and 3).
Test 2 (T2) - Assesses the learning outcomes of module 2 (chapters 4 and 5).
Both tests are mandatory. Minimum grade per test (module) of 7.5 values.
Final grade = 0.60 * T1 + 0.40 * T2
To obtain approval, in continuous evaluation, the student will have to obtain a grade equal to or greater than 7.5 in each of the modules and a weighted final grade equal to or greater than 9.5 values.
Assessment by normal or recourse exam:
Exam to evaluate both modules.
If the student, in the continuous evaluation, has obtained a minimum rating of 7.5 values in one of the modules, he/she can reuse the classification for that module. When performing proof only to one of the modules, the minimum score of 7.5 values remains. The approval in the curricular unit depends on obtaining a minimum of 9.5 values in the final weighted classification.
In examination for grade improvement, the reuse of classifications obtained in the continuous evaluation is not allowed.
Internship(s)
NAO
Bibliography
Murteira, B., Ribeiro, C., Silva, J., & Pimenta, F. (2015). Introdução à Estatística. Escolar Editora.
Guimarães, R., & Sarsfield Cabral, J. (2010). Estatística. Verlag Dashofer.
Reis, E., Melo, P., Andrade, R., & Calapez T. (2015). Estatística Aplicada, vol. 1. Edições Sílabo.
Reis, E., Melo, P., Andrade, R., & Calapez T. (2016). Estatística Aplicada, vol. 2. Edições Sílabo.
Pestana, D., & Velosa S. (2010). Introdução à Probabilidade e à Estatística, Vol. I. Lisboa: Fundação Calouste Gulbenkian.