Biostatistics

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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

1.1 History, Society and Science
2. Descriptive Statistics
2.1 Types of data
2.2 Tables and charts
2.3 Central and non-central tendency measures, dispersion measues, asymmetry and kurtosis measures
3. Probability Theory
3.1 Axioms
3.2 Bayes theorem
4. Random Variables
4.1 Discrete random variables
4.2 Continuous random variables
5. Sampling Theory
5.1 Fundamentals
5.2 Sampling design types
5.3 Law of large numbers
5.4 Central limit theorem
5.5 Sampling distributions
6. Experimental Design
6.1 Field studies
6.2 Natural and manipulative experiments
6.3 Replication and independence
6.4 Types of experimental design
7. Interval Estimation
8. Hypothesis Testing
8.1 Null and alternative hypothesis
8.2 Type I and II errors, power of the test and type of tests (one-tailed and two-tailed)
8.3 Parametric tests (for one or two population parameters)
8.4 Parametric one-way Analysis of Variance
9. Non-parametric Tests
9.1 Goodness-of-fit tests
9.2 Tests for the analysis of contingency table
9.3 Other tests
10. Correlation and Regression
10.1 Parametric and non-parametric correlation.
10.2 Simple and multiple linear regression

 

Teaching Methodologies

Theoretical classes

Lectures are used to present concepts, explore examples and solve problems. Assessment: Task I (individual) – Importance of Statistics and its Applications in Biological Sciences (two page A4 text); Task II (groups of three students) – Sampling and/or Experimental Design (two page A4 text and 10 minutes presentation); Quiz (problem solution).

Laboratorial classes

Use of computer tools in Descriptive Statistics and in Statistical Inference, namely the use of spreadsheets and statistical applications (e.g., Excel and SPSS). Tutorial files are given with protocol and data files. Students (groups of three) will be asked to write a scientific report to develop and assess different skills. Several problems are also solved regarding the taught subjects, which will be assessed with the aid of a computer.

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.

Rosner, B. (2010). Fundamentals of Biostatistics, 7th Edition. Brooks/Cole, Cengage Learning.

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

Zar, J. H. (2010). Biostatistical analysis, 5th Edition. Prentice-Hall International, Upper Saddle River, 662 pp.

Code

0105933

ECTS Credits

6

Classes

  • Práticas e Laboratórios - 30 hours
  • Teórico-Práticas - 30 hours