Course detail

LCE5871 - Residence in Statistical Analysis


Credit hours

In-class work
per week
Practice
per week
Credits
Duration
Total
1
2
4
15 weeks
60 hours

Instructor
Edwin Moises Marcos Ortega
Gabriel Adrian Sarries
Idemauro Antonio Rodrigues de Lara
Renata Alcarde Sermarini
Sônia Maria De Stefano Piedade
Taciana Villela Savian

Objective
To offer students in the Statistics and Agricultural Experimentation Program the opportunity to have direct contact with the real problems involved in experimentation. Develop statistical methods to solve problems in design and data analysis.

Content
Study, development and application of methods for planning and quantitative analysis of data inherent in observational and experimental studies, using computational resources. Exercise of writing protocols and technical reports of statistical assessments.

Bibliography
AGRESTI, A. Categorical data analysis. 3rd ed. New York: Wiley, 2012.
BARNETT, V. Sample Survey: Principles and Methods (3rd ed.). London: Arnold, 2002.
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. Analysisof longitudinal data. New York:Oxford University Press, 2002.
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.
LITTELL, R.C.; MILLIKEN, G.A.; STROUP, W.W.; WOLFINGER, R.D.; SCHABENBERGER, O. SAS for mixed models. SAS Institute Inc., Cary. 2006.
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.
NELDER, J.A. and WEDDERBURN, R.W.M. 1972.Generalized linear models. J. R. Stat. Soc. Ser. A Stat. Soc.135(Pt 3), 370–384.
MOLENBERGHS, G., & VERBEKE,G. Models for discrete longitudinal data. New York: Springer-Verlag, 2005.
PINHEIRO, J.C. and BATES, D.M. Mixed-Effects Models in S and S-PLUS, Springer, New York, NY, 2009.
RAO, C.R., TOUTENBURG,H., SHALABH, HEUMANN, C. Linear Models and Generalizations, 3rd ed. Springer, 2008.
R. Development Core Team. R: A languageandenvironment for statisticalcomputing. Vienna,Austria. Availablefrom: http://www.R-project.org.
SAS INSTITUTE INC. SAS/STAT ® 9.2 User’sGuide Procedures, 2008.
VENABLES, W.N. e RIPLEY, B.D. Statistics and Computing. Springer-Verlag. 2002. 495p