Biostatistics • HRB4031

 

RESPONSIBLE PROFESSORS:

Ivy Kiemle Trindade Suedam

Jeniffer de Cássia Rillo Dutka

Joel Ferreira Santiago Junior

 

CREDITS: 4

 

COURSE LOAD:

Theoretical
(per week)
Practical
(per week)
Studies
(per week)
Duration Total
4h 8h 3h 4 weeks 60h

OBJECTIVES:

Enable the student to apply and interpret statistical analysis procedures applicable to simple experimental models used in health research. 

The course emphasizes the principles and limitations as well as the assumptions and limitations involved in the different models of statistical analysis rather than on calculation procedures involved. 

We discuss the different levels of measurement in biomedical experiments and how they affect the model and interpretation of experimental results and the appropriate statistical model.  

 

BACKGROUND:

The current availability of computer programs and the difficulty of having any statistical advice has led many researchers to conduct their own analysis of the data not always in the most appropriate way. 

Thus, the correct choice of model used and its proper interpretation are more important than the work of calculation involved, which can undoubtedly be better executed in a computer. 

 

CONTENTS:

• Brief review of the concepts of mean, median, standard deviation, semi-quartile range and correlation
Brief review of probability concepts
Probability distributions: binomial, hypergeometric, Poisson, normal, chi-square, Student and F.
Test one mean, two independent means, and two paired means
Simple models of variance analysis: assumptions and requirements. Tests of more than two independent and paired means. Tests of more than two non-independent medium. Twoway Analysis of Variance: Interaction and additivity. Multiple comparisons. Contrasts. Correlation and regression.
Non-parametric analysis: general idea and applicability; Wilcoxon test; Mann-Whitney test; Kruskal-Wallis test; Friedman test; Non-parametric correlation; Spearman and Kendall.
Association tests: chi-square and Fisher
Testing one or two proportions
Odds ratio and relative risk

BIBLIOGRAPHY:

Arango HG. Bioestatistica: teórica e computacional com bancos de dados reais em disco. 3a ed. Rio de Janeiro: Guanabara Koogan; 2009.

Costa Neto PLO. Estatística. 2a ed. rev. atual. São Paulo: Edgard Blucher; 2002.

Downing D, Clark J. Estatística aplicada. 2a ed. São Paulo: Saraiva; 2002.

Hollander M, Wolfe D. Non parametric statistical methods. New York: John Wiley and Sons; 1973.

Kahn HA, Sempos CT. Statistical methods in epidemiology. New York: Oxford University; 1989.

Martinez EZ. Bioestatística para os cursos de graduação da área da saúde. São Paulo: Blucher; 2015.

Rosner B. Fundamentals of biostatistics. 6th ed. Belmont: Duxbury; 2005.

Spiegel MR, Stephens LJ. Estatística. Porto Alegre: Bookman; 2009.

Vieira S. Bioestatística: tópicos avançados. 2a ed. ver. atual. Rio de Janeiro: Campus; 2004.

Vieira S. Introdução a bioestatística. 5a ed. Rio de Janeiro: Elsevier; 2016.

Wasserman L. All of nonparametric statistics. New York: Springer; 2006.

Honório H & Santiago Junior. Fundamentos das revisões sistemáticas em Odontologia. 1ª ed. São Paulo: Quintessence; 2018.

 

 

<<< back to Syllabus index

 

Seção de Pós-Graduação HRAC-USP

Horário de atendimento: de segunda a sexta-feira, das 8h às 18h (exceto feriados) | e-mail: secpghrac@usp.br