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Code: MA214     Acronym: BIOE

Classification Keyword
OFICIAL Statistics

Instance: 2018/2019 - 3T (of 11-02-2019 to 29-03-2019) Ícone do Moodle

Active? Yes
Responsible unit: Population Studies
Course/CS Responsible: First Cycle Degree (BSc) in Aquatic Sciences

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
LCMA 30 Oficial Plan 2018 2 - 5 49 135

Teaching Staff - Responsibilities

Teacher Responsibility
Maria Margarida da Fonseca e Castro Cardoso

Teaching - Hours

Theoretical classes: 3,00
Practical classes: 4,00
Type Teacher Classes Hour
Theoretical classes Totals 1 3,00
Maria Margarida da Fonseca e Castro Cardoso 3,00
Practical classes Totals 2 8,00
Maria Margarida da Fonseca e Castro Cardoso 8,00

Teaching language



The main objective of this training program is that students acquire both theorethical and practical knowledge in basic biostatistics, through a process where they have to solve problems and the teacher function as guider in their individual pathway. The exposition to small biological problems will explore both theoretical and practical aspects of biostatistics, including verbal and written communication. Topics of Biostatistics include types of data, descriptive statistics, probability distributions and inference.

Learning outcomes and competences

After attending the course unit all students should be able to explore data using statistical measures and graphical methods; know how to apply simple statistical procedures autonomously; identify the types of statistical tests that can be applied in a given dataset, know the assumptions and know how to test them; know the limitations and strength of the conclusions obtained from the statistical analysis carried out; demonstrate the ability to analyze and systematize the information collected. Students should be able to convert data into information, gaining skills in quantitative reasoning and writing.

Working method



1. Descriptive Statistics: types of biological data; exploring data: variables and distributions, relationships. 2. Probability and sampling distributions. 3. Introduction to inference: estimation and hypothesis testing. 4. Statistical Inference with Quantitative Data: one sample t test, paired sample t test, independent sample t test. 5. Statistical Inference with Categorical Data: inference about a population proportion, comparing two proportions, qui-square test of independence, McNemar test. 6. Linear Regression. 7. Analysis of Variance: one-way and two-way analysis of variance.

Mandatory literature

Baldi Brigitte 070; practice of Statistics in the life science. ISBN: 1-4292-7272-4
Zar Jerrold H.; Biostatistical analysis. ISBN: 978-0-13-206502-3
Sokal Robert E.; Biometry. ISBN: 978-0-7167-2411-7

Teaching methods and learning activities

The teaching methods include the traditional face-to-face classes and an e-learning component. In the lecture sessions, the concepts of each module are introduced and reinforced by means of the resolution of small biomedical/biological problems. These face-to-face classes are combined with a Virtual Learning Environment (VLE). The use of an e-learning platform in Biostatistics allows the delivery of static and dynamic content to the students and also the on-line participation and evaluation. Weekly assignments are made at group level and consist in a small biological problem with a data file and a submission deadline. In the resolution of these weekly assignments, in a format similar to a short scientific paper, students have to report effectively both statistical and biological concepts, involved in their assignments. The examination is carried out in computers.



Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 75,00
Participação presencial 0,00
Trabalho de campo 5,00
Trabalho escrito 20,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 86,00
Frequência das aulas 49,00
Total: 135,00

Eligibility for exams

Students should attent at least 3/4 of the classes.

Calculation formula of final grade

Final grade: 0.75xE + 0.20xTG + 0.05*C E – Final exam (minimum 7.5); TG – Weekly assignments in the current academic year; C - Contributions.

Classification improvement

Final grade: 0.75xE + 0.20xTG + 0.05*C E – Final exam (minimum 7.5); TG – Weekly assignments in the current academic year; C - Contributions.
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