Statistics

Base Knowledge

Not applicable

Teaching Methodologies

Theoretical:

  1. Use of expository-active methodology easy to understand by the students.
  2. The display will focus on the identification and understanding of the basic concepts of Statistics and its relation with the Health field.
  3. Display of methods and statistical techniques according to the clinical reality and its transposition into the computer environment.

 

Theoretical-practical:

  1. Focuses on the application of knowledge learned in theory using statistical analysis Software (IBM SPSS Statistics).
  2. The student will benefit from a strong practical component in statistical analysis Software from the formation of databases, aggregation, transformation and its manipulation.
  3. 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

  1. General concepts: Descriptive Statistics and Inductive Statistics
  2. Sampling designs: Probabilistic/Random and non-Probabilistic Models
  3. Estimation of representative samples on the basis of the research design using Software.
  4. Data Reduction and Measuring Scales
  5. Descriptive Statistics: data tabulation, measures of central and non-central and dispersion tendency;
  6. Distribution Measures: Symmetry, Flattening and Normal Distribution and its properties to the inferential statistics
  7. Inductive Statistics: Estimation for Point, for Trust Intervals and Statistical Tests depending on the type of study (Analytical, Cohort and Experimental).
  8. Introduction and Application of Statistical Analysis Software): Creation of Databases, simulation of clinical phenomena according to the drawings of study (research).
  9. Application of statistical models, interpretation of results and its extrapolation for the population.

 

Curricular Unit Teachers

Internship(s)

NAO

Bibliography

1. Primary Bibliography

  1. Pestana, M.H.; Gageiro, J.N. “Análise de Dados para Ciências Sociais – A Complementaridade do SPSS”. Edições Sílabo, Lisboa: 1998.
  2. Zhou, X-H; Obuchowski, N.A.; McClish, D.K. “Statistical Methods in Diagnostic Medicine”. WILEY-INTERSCIENCE, a john wiley & sons, inc., publications. USA, 2002.
  3. Motulsky, H. “Intuitive Biostatistics”. Oxford University Press, New York, 1995.

 

2. Secondary Bibliography

  1. Rosner, B. “Fundamentals of Biostatistics”. Sixth Edition, International Student Edition. THOMSON, Brooks/Cole, USA, 2006.
  2. Motulsky, H. “Intuitive Biostatistics – A Nonmathematical Guide to Statistical Thinking”. Completely Revised, Second Edition, Oxford University Press, New York, 2010.
  3. Sabin, C.; Petrie, A. “Estatística Médica” 2.ª Edição, Roca, São Paulo, 2007.
  4. Levin, J.; Fox, J.A. “Estatística para Ciências Humanas”, 9.ª Edição, Pearson/Prentice Hall, São Paulo, 2004.