Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
2 |
2 |
8 |
15 weeks |
120 hours |
Instructor
Objective
Enable the student to plan, install, collect data and statistically analyze forest experiments. Also, the student will be able to prepare reports on forest experiments. Emphasis will be placed on the use of statistical software for data analysis.
Content
1. Importance of statistics in the forest area and relationships with other disciplines.
2. Software basics for statistical analysis of data.
3. The Normal distribution: origins, form and uses in the forest area. Asymmetry and Curtosis.
4. Comparison of two forest populations: the paired and unpaired t test
5. Basic principles of experimentation: repetition, randomization and local control. Assumptions of variance analysis.
6. Tabular analysis of forest data.
7. Completely randomized experiments
8. Experiments in randomized blocks.
9. The chi-square test.
10. Non-parametric tests.
11. Correlation analysis.
12 Soil-site relationship for implanted forests: simple and multiple linear regression.
Bibliography
CAMPOS, H. 1979. Estatística Experimental Não-Paramétrica. Piracicaba, FEALQ, 343 pp.
COCHRAN, W. G. & COX, G. M. 1957. Experimental Design. John Wiley & Sons, N.Iorque.
DAGNELIE, P. 1973. Estatística: Teoria e Métodos. Publicações Europa- América, Portugal. Vol. 1 e 2.
FONSECA, J. S. & MARTINS, G. A. 1986. Curso de Estatística. Ed. Atlas, São Paulo, 286 pp.
WALKER, G. 1997. Common Statistical Methods for Clinical Research with SAS® Examples, Cary, NC:SAS Institute Inc., 315 pp.
SNEDCOR, G. W. & W. G. COCHRAN. 1967. Statistical Methods. 6a Ed. Iowa State Univ., Ames, E.U.
SOKAL, R. R. & F.J. ROHLF. 1980. Biometry. Freeman, São Francisco. E.U.
ZAR, J.H. 1998. Biostatistical Analysis. Prentice Hall, 929 pp.