Teaching Methodologies
Classes consist of a theoretical exposition of the subject, accompanied by practical examples so that there is a better understanding of it. The resolution of practical exercises is done using the SPSS computer support, thus making it possible to apply the material taught to real cases Students are provided a theoretical support so that they can follow the subjects taught. The clarification of questions is done in fixe schedule Classes may have a maximum percentage of 70% in online teaching The continuous evaluation of knowledge is carried out based on two time points. The final continuous evaluation is the weighted average of the two time points, and the weight of each test is 6 and 14. The student cannot perform the 2nd
test if you have obtained a minimum score of 7.5 points (0-20 points) in the 1st test. The approval in the discipline is
obtained with a minimum classification of 10 values.
The provisions of the A. R. in force with regard to access to Exam Times will be fulfilled.
Learning Results
The student should acquire skills to understand the underlying applicability of the theoretical models used for statistical analysis as well as analyse and interpret the results obtained. Students should also be able to use the computer software SPSS to solve problems involving the concepts developed in the course.
The student should acquire the basic skills for conducting studies for quantitative analysis, also critical appreciation and proper interpretation of the results of an inferential study.
Program
Chapter 1 – Descriptive Statistics
1.General Concepts
population, sample and individuals
types of measurement
types of statistics
2 Descriptive Statistics
Tables of frequencies
Graphical representation
Statistics
measures of central tendency
dispersion measurements
Skewness and Kurtosis measurements
3. Introduction to statistical software SPSS
Chapter 2 – Hypothesis Testing (Statistical hypothesis, errors classification and significance levels of tests with normal
distribution, type tests)
Chapter 3 – Strategies for statistical treatment of the data
Chapter 4 – Parametric tests
Requirements for the use of parametric tests
Criteria of choice
Parametric Statistics
One-sample t-test
Two-sample t-tests for a difference in mean
Analysis of variance – ANOVA
Correlation and Regression
Chapter 5 – Nonparametric Statistics
Paired samples: Friedman, Wilcoxon and McNemar
Independent samples: Mann-Whitney and Kruskal-Wallis H
Internship(s)
NAO
Bibliography
A. Gouveia de Oliveira (2009). Bioestatística, Epidemiologia e Investigação – teoria e aplicações, Lidel.
Cecília Moura Silva (1994). Estatística aplicada à psicologia e ciências sociais, McGraw-Hill.
Francisco Mercês de Mello, Rita Cabral Guimarães (2015). Métodos Estatísticos para o Ensino e a Investigação nas Ciências da Saúde, Edições Sílabo.
Gilda Cunha, Mª do Rosário Martins, Ricardo Sousa, Filipa Ferraz de Oliveira.(2007). Estatística aplicada às ciências e tecnologias da saúde, Lidel.
Joaquim Pinto Coelho, Inês Legatheaux Martins, Luísa Margarida Cunha (2008), Inferência Estatística – Com utilização do SPSS e G*power, Edições Sílabo.
João Maroco (2003). Análise estatística com utilização do SPSS, Edições Sílabo.
Pedro Marques Vidal (2005). Estatística prática para as ciências da saúde, Lidel.