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Statistical methods in health sciences

Code: PDCCV_3     Acronym: PDCCV_3

Keywords
Classification Keyword
OFICIAL Public Health

Instance: 2015/2016 - 1S Ícone do Moodle

Active? Yes
Responsible unit: Physiology and Cardiothoracic Surgery Department
Course/CS Responsible: Doctoral Programm in Cardiovascular Sciences

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
PDCCV 10 Ciências Cardiovasculares_13 1 - 4 18 108

Teaching Staff - Responsibilities

Teacher Responsibility
Milton Severo Barros da Silva

Teaching - Hours

Theoretical classes: 0,93
Laboratory Practice: 0,36
Type Teacher Classes Hour
Theoretical classes Totals 1 0,93
Milton Severo Barros da Silva 0,93
Laboratory Practice Totals 1 0,36
Milton Severo Barros da Silva 0,36

Teaching language

Suitable for English-speaking students

Objectives

Acquisition of knowledge on the primary and most used statistical concepts, models and techniques. Choice and application of the most adequate statistical methodology according to the nature of the study.  Ability to critically analyse and interpret the results obtained from the learnt statistical methods (in their own works and in those from others). In summary, the student is expected to be scientifically autonomous regarding basic statistical analysis.

Learning outcomes and competences

The student will: acquire skills to select the most adequate statistical analysis for each study; perform the statistical analysis on SPSS and understand the mathematical/statistical/probabilistic model behind; critically interpret the obtained results. 

 

Working method

Presencial

Program

Probabilities, conditional probabilities and the usual probabilistic models (Uniform, Binomial, Poisson, Multinomial, Normal, t, F, Qui-Squared). Descriptive statistics: numerical statistical measures and graphical representations. (Weak) Law of the large numbers and the central limit theorem. Sample statistics and confidence intervals, for one and two samples. Tests of hypotheses (parametric and non-parametric) for one and two samples and for continuous and categorical data. Linear correlation and Spearman correlation. Multiple linear regression: the model and its hypotheses, hypotheses tests and confidence intervals for the model parameters, prediction intervals, coefficient of determination, multicollinearity, model comparison and some diagnostic methods.

Mandatory literature

A. Rita Gaio; apontamentos escritos preparados pela professora
B. Rosner; Fundamentals of Biostatistics, Brooks Cole, 2005

Complementary Bibliography

M.Bland and D. Altman; An Introduction to Medical Statistics, Oxford University Press, 2000. ISBN: 0 19 262428 8
G. van Belle, P.J. Heagerty, L.D. Fisher, T.S. Lumley; Biostatistics: A Methodology for the Health Sciences, John Wiley & Sons Inc, 2004

Teaching methods and learning activities

A total of 108 hours of student’s work, of which 36 are of contact, distributed as follows is estimated:

A weekly theoretical session of 90 min (total: 9 sessions – 13.5h)
A theoretical-practical weekly session of 120 min (9 sessions total – 22.5h)

Software

SPSS

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 75,00
Trabalho escrito 25,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 72,00
Frequência das aulas 36,00
Total: 108,00

Eligibility for exams

To be present in at least 75% of the classes

Calculation formula of final grade

 

Final mark (out of 20) = exam classification (out of 15) + assignment classification (out of 5)

The above formula is only applicable if the student gets more than 4.5 values (in 15) in the written examination; otherwise, the student fails the curricular unit, independently from the mark obtained in the written homework.

The written assignment can be done individually or in a group of 2 elements.
 

Classification improvement

The exam classification can be improved on the 2nd period of examination. The classification obtained in the assignment cannot be improved.

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