Applied Engineering Mathematics II

In theoretical-practical lessons the expository and inquisitive method is used during the explanation of the theoretical subjects. Examples of real data are presented and exercises are resolved as concept’s application.
In laboratorial classes students should practicing the concepts with the resolution of exercises in groups and individually, using appropriate software whenever it deems necessary. In addition, students will be supervised, through the clarification of theoretical doubts and exercises resolution.

Objectives: Realizing the importance of the relationship between a set of variables. Know how to establish the most appropriate regression model to a real data set. Know methods for solving an optimization problem.
Generic skills: Application of the knowledge and understanding; self-learning. Critical thinking. Interpretation of results. Communication. Work in groups.
Specific skills: To learn the Least Squares Meth. to obtain the linear regression model; understanding the regression parameters and coefficient of determination. To make statistical inferences about these parameters.
To use the more convenient regression models to adjust a set of variables related to problems of engineering.
To understand that the need to get the best out of a system is a very strong motivation; the importance of obtain
the maximum amount of product or to minimize the cost of a process. To know the Linear Programming
problem. To use the simplex algorithm. Knowing how to use appropriate software.

Part I – Regression
Review of some important probability models in statistical inference.
Hypothesis Testing. Parametric Tests and Non parametric Tests.
Regression. Simple Linear Regression. Least Squares Estimators of the Regression Parameters. Statistical Inference about the regression parameters. The coefficient of determination and the sample correlation.
Analysis of residuals: Assessing the Model. Transforming to Linearity. Multiple Linear Regression. Use of statistical software SPSS in Regression.
Part II – Optimization
Optimization. Linear Programming. Simplex Algorithm. Examples in civil engineering. Use of Solver Supplement of Microsoft Excel.

NAO