Biostatistics
Objectives
The teaching of this curricular unit aims to promote the acquisition of knowledge about the basic
concepts of statistics. Additionally, students will be introduced to the Statistical Package for the
Social Sciences (SPSS). It is an easy-to-use statistical software that will enable students to analyse
data obtained from epidemiology studies, by the implementation of the theoretical statistical
methods previously learned. This curricular unit should promote the following skills: a) to know
the basic functionalities of SPSS that will allow students to: b) do an exploratory analysis, and c)
implement the hypotheses tests after identifying which is the most appropriate. Additionally,
students should be able to read more easily scientific papers and with a better understanding of
the results, particularly in the academic area of the curricular unit.
General characterization
Code
107023
Credits
4
Responsible teacher
Ana Luisa Trigoso Papoila da Silva,SOFIA ALEXANDRA FRIAS MENDES DA GRACA POETA,SUSANA ISABEL MATEUS SANTOS
Hours
Weekly - Available soon
Total - 112
Teaching language
PT
Prerequisites
Available soon
Bibliography
Available soon
Teaching method
Teaching is based in the integration of theoretical teaching where themes are presented by a
teacher and students are encouraged to participate, and practical teaching through the resolution
of practical exercises using SPSS. Therefore, the classes will be theoretical-practical and directed
to small groups of students. Interaction between students and teachers is both at the classroom
and by e-mail. Classes will take, at most, 180 minutes and will take place at a classroom with
computers (one for each student).
Evaluation method
Students¿ performance assessment will be summative with a
final written exam in which most of the exercises must be solved using SPSS.
Subject matter
Summarizing data. Presenting data. Correlation coefficients (Pearson, Spearman, and Kendall).
Normal, Student¿s t, Chi-Squared, and Snedecor's F distributions. Sampling methods.
Questionnaires. Statistical inference: estimation and hypotheses tests: basic concepts, one-sample
tests, two independent samples tests (z test, t test, and Mann-Whitney test), paired samples tests
(paired t-test, Wilcoxon, and Sign test), more than two independent samples tests (ANOVA I and
Kruskal-Wallis) and more than two related samples test (Friedman). Analysis of cross-tabulations
(Chi-squared test for association and Fisher's exact test) and McNemar's test for matched samples.
Interpreting results obtained by linear, logistic and Cox regression models. SPSS functionalities that
will enable students to analyse the data with the statistical methodologies previously taught.