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Biostatistics

Code: MNCSP1107     Acronym: BIOEST

Keywords
Classification Keyword
OFICIAL Statistics

Instance: 2020/2021 - 1S Ícone do Moodle

Active? Yes
Course/CS Responsible: Master in Community Nutrition and Public Health

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MNCSP 18 Official plan 1 - 4 36 108

Teaching Staff - Responsibilities

Teacher Responsibility
Maria Margarida da Fonseca e Castro Cardoso

Teaching - Hours

Theoretical classes: 1,29
Laboratory Practice: 1,29
Type Teacher Classes Hour
Theoretical classes Totals 1 1,29
Maria Margarida da Fonseca e Castro Cardoso 1,29
Laboratory Practice Totals 1 1,29
Maria Margarida da Fonseca e Castro Cardoso 1,29

Teaching language

English

Objectives

The main objective of this training program is that students acquire both theorethical and practical knowledge in basic biostatistics.

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.

Working method

Presencial

Program

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.

Mandatory literature

Baldi B., D.S. Moore; The practice of statistics in the life sciences, W.H. Freeman and Company, 2012
Sokal R. , F.J. Rohlf; Biometry – The principles and practice of statistics in biological research, W.H. Freeman and Company, 2012
Zar J.H.; Biostatistical Analysis, Prentice - Hall International Inc., 2010

Teaching methods and learning activities

The teaching methods include the traditional face-to-face classes. In the lecture sessions, the concepts of each module are introduced and reinforced by means of the resolution of small biomedical/biological problems. In the practical component the students resolve several problems, with emphasis on the correct formulation of the statistical problems proposed and in the interpretation of results. Students  should provide  the  scope,  purpose  and  rationale  of the study; should identify and  describe  the  statistical  methods, considering the necessary assumptions, state the  statistical  significance  level  considered and  specify  the  computer  program  used; students  should  be  able to report adequately the important trends and main results observed in their data analysis; and should  indicate the  interpretation  of  the  main  results  and  the conclusions. The  final  exam includes several problems. The  resolution of the problems requires  the  same  skills  necessary  for  the  resolution  of  the  exercises proposed to the students in the practical component of the course.

Software

SPSS

Evaluation Type

Evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 100,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Frequência das aulas
Total: 0,00

Eligibility for exams

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

Calculation formula of final grade

Final Exam.
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