Statistical Inference

Basic information

Workload: 

60 hours

Prerequisite: 

Probability Theory

Syllabus: 

Statistical inference, a priori and posteriori distributions, conjugated prioris, Bayes estimators, maximum likelihood estimators and their properties, sufficient statistics; Distributions of the sample mean and variance (Chi-square and t), Confidence intervals, Non-biased estimators; Basic theory of hypothesis testing, t test, F test; Introduction to linear models.

 

Teaching Plan

Bibliography

Mandatory: 

•    Bussab, W. de O. and Pedro A. Morettin. Basic Statistics. São Paulo: Ed. Saraiva. 5th. ed. 2003
•    Versani, John. Using R for Introductory Statistics. Chapman & Hall, 2005 (online version at http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf)
•    Morris DeGroot, Mark Schervish. Probability and Statistics. Fourth Edition, 2012.
 

Complementary: 

•    Meyer, Paul L .. Probability: applications to statistics. Technical and Scientific Books, 1983.
•    Mood, Alexander M., Graybill, Franklin A; Boes, Duane C. Introduction to the theory of statistics. 3. rd ed.. New York: McGraw-Hill, 1974. 564 p.
•    Bickel, P. J.; Doksum, K. A. Mathematical statistics: basic ideas and selected topics. Oaklan, Calif.: Holden Day, 1977. 492p.
•    Larson, H. J. Introduction to probability theory and statistical inference. 3rd. Ed. New York: Wiley, 1982. 637p.
•    David S. Moore. Basic statistics and its practice. Technical and Scientific Books, 2005.