Statistics

Not applicable.

Theoretical:

• Use of expository-active methodology easy to understand by the students.

• The display will focus on the identification and understanding of the basic concepts of Statistics and its relation with the Health field.
• Display of methods and statistical techniques according to the clinical reality and its transposition into the computer environment.

2nd Theoretical-practical component:

• The application of knowledge learned in theory with the use of statistical analysis software is privileged.
• The student will benefit from a strong practical component in statistical analysis software since the formation of databases, aggregation, transformation and manipulation.
• Application of different models of statistical analysis using specialized software.

3rd Practical Strand:

• Practical statistics exercises with examples related to environmental health and health in general are privileged.

1. The student must acquire knowledge of:

       Analytical Methods and Techniques in Statistics that allow the understanding of different health phenomena.
       Sample Estimation Method and its test power depending on the different research designs that the student can be confronted with in the medical, clinical and laboratory scope.
       Data Analysis Software in Statistics.

    

   The student must acquire skills in:

       Estimation of Samples on population/sample, experimental, cohort and case-control parameters.
       Creation of “Databases”, manipulation of clinical and laboratory indicators (exams, samples, analytical parameters, measurement scales, etc.) and interpretation of results.

    

   The student must acquire skills in:

       Decision on Statistical Analysis Models for the study of real facts (prevalence/diagnosis), prediction of results (prognosis) and choice of indicators/indices (multivariate methods).
       Validation of diagnostic and prognostic methods in the clinical setting.
       Analysis and interpretation of results manipulated in statistical analysis software.

General Concepts: Descriptive Statistics and Inductive Statistics; Sample Designs: Probabilistic/Random and Non-Probabilistic Models; Estimation of representative samples depending on the research design (10h).

Data Reduction and definition of Measurement Scales; Descriptive Statistics Measures: data tabulation, measures of central and non-central tendency and dispersion; Distribution Measures: Symmetry, Flatness and Normal Distribution and their properties for inferential statistics (20h).

Inferential Statistics Measures: Point Estimation and Statistical Tests depending on the type of study (Analytical, Cohort and Experimental): Cohen’s Kappa test; McNemar test; Wilcoxon T test; Student’s t-Test for Paired Samples; ANOVA test for repeated measures to Factor I and respective tests of Multiple Comparisons; Friedman’s non-parametric ANOVA test and respective Multiple Comparisons test. Student’s t-Test for 1 Sample; Adherence Chi-square Test; Pearson’s chi-square test; Pearson’s Chi-square Test with Yates’ Continuity Correction and Fisher’s test; Wilcoxon-Mann-Whitney test; t-Student Test for Independent Samples and Levene Test; One-way ANOVA test for the respective Multiple Comparisons test; Kruskal-Wallis non-parametric ANOVA test and respective Multiple Comparisons test. Correlation Tests: Introduction to Covariance; Pearson’s Linear Correlation Coefficient; Spearman’s Ordinal Correlation Coefficient. Introduction and Application of Statistical Analysis Software: Creation of Databases, simulation of clinical phenomena according to study designs (research). Application of statistical models, interpretation of results and their extrapolation to the population (45h).

NAO

Bibliografia Primária

1. Vet, H.C.; Terwee, C.B.; Mokkink, L.B.; Knol, D.L. Measurement in Medicine – Pratical Guide to Biostatistics and Epidemiology. Cambridge University Press, 7th Printing, United Kingdom, 2016.

2. Motulsky, H. “Intuitive Biostatistics – A Nonmathematical Guide to Statistical Thinking”. Completely Revised, Second Edition, Oxford University Press, New York, 2010.

3. Cunha, G.; Martins, M.R.; Sousa, R.; Oliveira, F.F. Estatística Aplicada às Ciências e Tecnologias da Saúde. Lídel: Lisboa, 2007.

4. Pestana, M.H.; Gageiro, J.N. Análise de Dados para Ciências Sociais – A complementaridade do SPSS. 4.ª Ed., (Revista e Aumentada), Edições Sílabo: Lisboa, 2005.

5. Vidal, P.M. “Estatística prática para as ciências da saúde”. Lidel, Lisboa, 2005.

6. Kirkwood, B., Sterne, J. Essentials of Medical Statistics. 2.nd edition. Wiley-Blackwell, 2001.

Bibliografia Secundária

1. Mello, F.C.; Guimarães, R.C. Métodos Estatísticos para o Ensino e a Investigação nas Ciências da Saúde. Edições Sílabo: Lisboa, 2015.

2. Hall, A.; Neves, C.; Pereira, A. Grande Maratona de Estatística no SPSS. Escolar Editora: Lisboa, 2011.

3. Elizabeth Reis, Rosa Andrade, Teresa Calapez e Paulo Melo. Exercícios de Estatística Aplicada – Vol. 2 (3ª Edição revista e corrigida). Editor: Edições Sílabo, Edição: janeiro de 2021

4. Marôco, J. Análise Estatística com o SPSS Statistics. 8.ª Edição, Lisboa, 2012. Editor: ReportNumber, Edição: Março de 2021

5. Figueiredo, F. Estatística Descritiva e Probabilidades – Problemas Resolvidos e Propostos com Aplicações em R (2ª Edição). Editor: Escolar Editora; Edição: outubro de 2009