Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
1 |
1 |
4 |
15 weeks |
60 hours |
Instructor
Clarice Garcia Borges Demetrio
Fábio Prataviera
Idemauro Antonio Rodrigues de Lara
Renata Alcarde Sermarini
Sônia Maria De Stefano Piedade
Taciana Villela Savian
Objective
To provide students in the Statistics and Agronomic Experimentation program with the opportunity for direct engagement with real-world problems related to experimentation. To develop statistical methods aimed at solving challenges in data planning and analysis, as well as applying advanced techniques for interpreting and exploring these data.
Content
Study, development, and application of methods for planning and quantitative analysis of data inherent to observational and experimental studies, utilizing computational resources. Practice in writing protocols and technical reports for statistical consulting.
Bibliography
AGRESTI, A. Categorical data analysis. 3rd ed. New York: Wiley, 2012.
BARNETT, V. Sample Survey: Principles and Methods (3rd ed.). London: Arnold, 2002.
Box, G. E. P., Jenkins, G.M., Reinsel, G.C. and Ljung, GM. (2015). Time Series Analysis: Forecasting
and Control, 5th Edition. Wiley.
CHRISTENSEN, W. F., RENCHER, A. C. Methods of Multivariate Analysis, 3rd Edition, Wiley: 2012.
Cox, D.R.; Donnelly, C.A. (2011). Principles of Applied Statistical. Cambridge, Cambridge University Press.
DIGGLE, P. J., P. J. HEAGERT, K. Y. LIANG, and S. L. ZEGER. Analysis of longitudinal data. New York:Oxford University Press, 2002.
Jiawei, H., Kamber, M. and Pei, J. Data mining: Concepts and techniques, 3rd ed. Elsevier, 2012.
KLEINMAN, K., HORTON, N. SAS and R: Data Management, Statistical Analysis and Graphics. CRC Press, 2010.
LAWLESS, J. F. Statistical Models and Methods for Lifetime Data. John Wiley and Sons, New York. 2003.
MANLY, B.F. Multivariate Statistical Methods: a primer, CHAPMAN & HALL. London, UK, 2004.
MONTGOMERY, D. C. Desgn and Analysis of Experiments, 8 ed. Wiley.
MONTGOMERY, D.C.; PECK, E.A.; VINING, G.G. 5rd. Introduction to Linear Regression Analysis. John Wiley, Nova Iorque. 2012.
MCCULLAGH, Peter. Generalized linear models. Routledge, 2019.
MOLENBERGHS, G., & VERBEKE,G. Models for discrete longitudinal data. New York: Springer-Verlag, 2005.
RAO, C.R., TOUTENBURG,H., SHALABH, HEUMANN, C. Linear Models and Generalizations, 3rd ed. Springer, 2008.
Sharon, L. Lohr. Sampling: Design and Analysis, 2nd ed. 2019
VENABLES, W.N. e RIPLEY, B.D. Statistics and Computing. Springer-Verlag. 2002. 495p