Base Knowledge
Not applicable
Teaching Methodologies
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.
Theoretical-practical:
- Focuses on the application of knowledge learned in theory using statistical analysis Software (IBM SPSS Statistics).
- The student will benefit from a strong practical component in statistical analysis Software from the formation of databases, aggregation, transformation and its manipulation.
- Application of different models of statistical analysis using specialized Software.
Learning Results
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 Potency according to the different research designs that the student can be confronted with in the medical, clinical and laboratory scope.
- Contact with Data Analysis software in Statistics.
The student must acquire skills of:
- Sample Estimation on population / sample, experimental, cohort and case-control parameters.
- Creation of “Databases”, manipulation of clinical and laboratory indicators (exams, harvests, analytical parameters, measurement scales, etc.) and interpretation of results.
The student must acquire skills of:
- Decision of Statistics 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 field.
- Analysis and interpretation of results manipulated in statistical analysis software.
Program
- General concepts: Descriptive Statistics and Inductive Statistics
- Sampling designs: Probabilistic/Random and non-Probabilistic Models
- Estimation of representative samples on the basis of the research design using Software.
- Data Reduction and Measuring Scales
- Descriptive Statistics: data tabulation, measures of central and non-central and dispersion tendency;
- Distribution Measures: Symmetry, Flattening and Normal Distribution and its properties to the inferential statistics
- Inductive Statistics: Estimation for Point, for Trust Intervals and Statistical Tests depending on the type of study (Analytical, Cohort and Experimental).
- Introduction and Application of Statistical Analysis Software): Creation of Databases, simulation of clinical phenomena according to the drawings of study (research).
- Application of statistical models, interpretation of results and its extrapolation for the population.
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
1. Primary Bibliography
- Pestana, M.H.; Gageiro, J.N. “Análise de Dados para Ciências Sociais – A Complementaridade do SPSS”. Edições Sílabo, Lisboa: 1998.
- Zhou, X-H; Obuchowski, N.A.; McClish, D.K. “Statistical Methods in Diagnostic Medicine”. WILEY-INTERSCIENCE, a john wiley & sons, inc., publications. USA, 2002.
- Motulsky, H. “Intuitive Biostatistics”. Oxford University Press, New York, 1995.
2. Secondary Bibliography
- Rosner, B. “Fundamentals of Biostatistics”. Sixth Edition, International Student Edition. THOMSON, Brooks/Cole, USA, 2006.
- Motulsky, H. “Intuitive Biostatistics – A Nonmathematical Guide to Statistical Thinking”. Completely Revised, Second Edition, Oxford University Press, New York, 2010.
- Sabin, C.; Petrie, A. “Estatística Médica” 2.ª Edição, Roca, São Paulo, 2007.
- Levin, J.; Fox, J.A. “Estatística para Ciências Humanas”, 9.ª Edição, Pearson/Prentice Hall, São Paulo, 2004.