Statistic

It uses an expository-active methodology that is easy for students to understand.Theoretical-practical aspect: The application of the knowledge learned in theory is privileged, using calculation and statistical analysis software.
– Continuous evaluation:
Students will take two tests (written tests). Students who obtain a classification < 7.5 points (Scale from 0 to 20 points) in the 1st Frequency are prohibited from participating in the 2nd evaluation moment. The final grade will result from the average of the ratings obtained in the two evaluations by frequency. Students with a final average ≥ 9.5 (scale from 0 to 20) will be exempted from the final exam.
– Assessment by exam:
In the Assessment by exam it will cover all the material taught in the discipline. Rating ranges from a scale of 0 to 20 values.

Knowledge:
Analytical Methods and Techniques in Statistics that allow the understanding of health phenomena. Sample Estimation Method and its Testing Power in function of the different research designs that the student may be confronted in health scope. Different Statistical Data Analysis Software.
Skills:
Estimation of Samples on population/sample, experimental, cohort and case-control parameters. Creation of “Databases”, manipulation of health indicators (exams, collections, analytical parameters, measurement scales, etc.) and interpretation of results.
Competences:
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.
– Data Reduction and definition of Measurement Scales; Descriptive Statistics Measures: data tabulation, measures of central and non-central tendency and dispersion; Distribution Measures: Symmetry, Flattening and Normal Distribution and their properties for inferential statistics.
– Inductive Statistical Measures: Point Estimation, Confidence 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 depending on study designs (research). Application of statistical models, interpretation of results and their extrapolation to the population.

NAO