DEPARTAMENTO DE FÍSICA

Biostatistics - EB

Ano letivo: 2017-2018

Specification sheet

Specific details

course code | cycle os studies | academic semester | credits ECTS | teaching language |

1003650 | 1 | 1 | 4.5 | pt |

Learning goals

To analyze data using appropriate statistical procedures;

To use suitable software tools to perform statistical calculations;

To plan correctly statistical studies in biomedical sciences;

To judiciously evaluate the results of studies published in the literature;

To use suitable software tools to perform statistical calculations;

To plan correctly statistical studies in biomedical sciences;

To judiciously evaluate the results of studies published in the literature;

Syllabus

Introduction to exploratory data analysis: level of measurement, measures of location and dispersion.

Descriptive statistics and data visualization: numerical indicators and graphics. Databases: creation, labeling and debugging.

Probability: concept and algebra. Random variables and probability functions. Discrete probability distributions: binomial and Poisson. Continuous probability distributions: normal, normal standard and t-Student. Central limit theorem.

Inferential statistics. Sample, population and sampling techniques. The estimation theory: point estimation and confidence intervals.

Statistical hypothesis and hypothesis testing. Level of significance and power of a test. P value. Parametric and non-parametric tests.

Methods of regression and correlation;

Statistical methods of supervised and unsupervised classification.

Descriptive statistics and data visualization: numerical indicators and graphics. Databases: creation, labeling and debugging.

Probability: concept and algebra. Random variables and probability functions. Discrete probability distributions: binomial and Poisson. Continuous probability distributions: normal, normal standard and t-Student. Central limit theorem.

Inferential statistics. Sample, population and sampling techniques. The estimation theory: point estimation and confidence intervals.

Statistical hypothesis and hypothesis testing. Level of significance and power of a test. P value. Parametric and non-parametric tests.

Methods of regression and correlation;

Statistical methods of supervised and unsupervised classification.

Prerequisites

Generic skills to reach

. Competence in analysis and synthesis;. Competence in organization and planning;

. Competence for working in group;

. Critical thinking;

. Competence in applying theoretical knowledge in practice;

. Competence to solve problems;

. Competence in working in interdisciplinary teams;

. Competence in autonomous learning;

. Self-criticism and self-evaluation;

(by decreasing order of importance)

Teaching hours per semester

lectures | 15 |

laboratory classes | 30 |

tutorial guidance | 15 |

total of teaching hours | 60 |

Assessment

Laboratory or field work | 25 % |

Problem solving | 25 % |

Exam | 50 % |

Bibliography of reference

Análise Estatística, com utilização do SPSS; João Maroco, Edições Silabo;

Fundamentals of Biostatistics, Bernard Rosner, Thomson Brooks/Cole, 2006

Bioestatística, Epidemiologia e Investigação, A. Gouveia de Oliveira, Lidel

Métodos Quantitativos em Medicina, Massad, Menezes, Silveira & Ortega ed. Manole, 2004

Pattern Classification; Richard Duda, Peter Hart, David Stork; John Wiley & Sons, Inc

An Introduction of Support Vector Machines; Nello Christianini, John Shawe-Taylor; Cambridge University Press

Fundamentals of Biostatistics, Bernard Rosner, Thomson Brooks/Cole, 2006

Bioestatística, Epidemiologia e Investigação, A. Gouveia de Oliveira, Lidel

Métodos Quantitativos em Medicina, Massad, Menezes, Silveira & Ortega ed. Manole, 2004

Pattern Classification; Richard Duda, Peter Hart, David Stork; John Wiley & Sons, Inc

An Introduction of Support Vector Machines; Nello Christianini, John Shawe-Taylor; Cambridge University Press

Teaching method

Lecturing, demonstrating, discussion and practical problem resolution.

Resources used

Sala com computadores e aplicação estatística SPSS