Biostatistics

Objectives

Learning goals (LG)

1. Contextualize statistics in society and in science

2. Understand the fundamentals of descriptive statistics

3. Recognize the importance of probability theory

4. Understand the concept of random variable

5. Understand the fundamentals of sampling theory and of experimental design

6. Understand the mechanic of hypothesis testing

7. Distinguish parametric and non-parametric tests

8. Distinguish correlation and regression

9. Recognize Bayesian inference

Skills

General (GS)

1. Team work

2. Bibliographic search and synthesis

3. Communicate scientific information

4. Write a scientific report

Specific (SS)

1. Develop statistical reasoning

2. Apply descriptive statistics

3. Simulate random variables

4. Apply sampling distributions

5. Estimate confidence intervals

6. Apply hypothesis testing

7. Use computer tools in statistics

Program

1. (Bio)Statistics

History, society and science

2. Descriptive statistics

Types of data

Tables and charts

Measures of central tendency and of variability

3. Probability theory

Axiomes

Bayes theorem

4. Random variables (RV)

Discrete RV

Continuous RV

5. Sampling theory

Fundamentals

Types of sampling

Law of large numbers

Central limit theorem

Distribuições amostrais

6. Experimental design

Fileld studies

Natural and manipulative experiments

Replication and independence

Types of experimental design

7. Interval estimation

Confidence and credibility intervals

8. Hypothesis testing

Null and alternative hypothesis

Type I and II errors

Power of the test

One-tailed and tow-tailed tests

Analysis of variance

9. Non-parametric tests

Fit tests

Contingency table analysis

Other tests

10. Correlation and regression

Parametric and non-parametric correlation.

Simple linear regression

11. Bayesian models

Teaching Methodologies

Theoretical sessions. Lectures are used to present concepts, explore examples and solve problems. Assessment: Task I (individual) – Importance of Statistics (two page A4 text); Task II (groups of 3 students) – Random variables (two page A4 text and 10 minutes power point presentation); Exam (problem solution). Practical sessions. Use of computer tools in descriptive statistics and in statistical inference: spreadsheet and statistical applications (SPSS and WinBUGS). Tutorial files are given with protocol, data and expected results. Students (groups of 3) write a scientific report to develop and assess different skills (GS1-4). Several problems are solved regarding the taught subjects, what is assessed through a computer practical exam.

Bibliography

Gouveia de Oliveira, A. (2009). Bioestatística, Epidemiologia e Investigação. Teoria e aplicações - Uma nova abordagem sem equações matemáticas. Lisboa: Lidel.

Gotelli, N. J. & A. M. Ellison (2004). A primer of Ecological Statistics. Sinauer Associates, Inc., Sunderland, 510 pp.

Maroco, J. (2010). Análise estatística com a utilização do SPSS. 3ª Edição. Edições Sílabo, Lisboa, 822 pp.

McCarthy, M. A. (2007). Bayesian Methods for Ecology. Cambridge University press, Cambridge, 296 pp.

Pestana, D. D. e Velosa, S. (2010). Introdução à Probabilidade e à Estatística, 4ª edição. Calouste Gulbenkian, Lisboa, 1164 pp.

Stigler, S. M. (1986). The history of statistics. The measurment of uncertainty before 1900. Belknap Press, Harvard University Press, Cambridge, 410 pp.

Zar, J. H. (1996). Biostatistical analysis. Prentice-Hall International, Upper Saddle River, 662 pp.