# Course detail

### LCE5801 - Regressão e Covariância

__Credit hours__

In-class work per week |
Practice per week |
Credits |
Duration |
Total |

3 |
1 |
8 |
15 weeks |
120 hours |

__Instructor__

Clarice Garcia Borges Demetrio

Silvio Sandoval Zocchi

Taciana Villela Savian

__Objective__

The discipline of regression and covariance is intended to provide students with a solid foundation of the theory of regression as well as applications in various areas. At the end of the course the student will be able to adequately use the methods of estimation of parameters of the models of regression and covariance, perform an analysis for diagnosis and analysis of residues, use the methods of selection of variables, perform tests of hypotheses about the parameters of the models and obtain the confidence intervals and prediction.

__Content__

Simple linear regression: statistical model, estimated by the method of least squares, properties of the estimators, hypothesis testing and confidence intervals for the parameters, interval estimates. Generalization by the method information display. Multiple linear regression analysis: statistical model, estimated by the method of least squares, properties of the estimators, hypothesis testing and confidence interval for parameters, selection of variables. Orthogonal polynomials. Analysis of residues and diagnostics. Estimation of parameters in normal distribution bivariate analysis by the method of maximum likelihood. Correlation coefficients, simple, partial and multiple: pets, hypothesis testing and confidence intervals. Tests of parallelism of straight. Exponential regression. Logistic regression. Regression of mitscherlich. Analysis of covariance. Introduction to generalized linear models.

__Bibliography__

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Chatterjee, S.; , A. S. Had. Regression Analysis by Example.. Edição 5, Ed. John Wiley & Sons, 2013, 424p.

Montgomery, D. C.; E. A. Peck, G. G. Vining. Introduction to Linear Regression Analysis. 5a ed. Ed. John Wiley & Sons, 2015, 672p.

Montgomery, D. C.; E. A. Peck, G. G. Vining. Solutions Manual to Accompany Introduction to Linear Regression Analysis. 5a ed. Ed. John Wiley & Sons, 2015, 164p.