Statistical Methods

Basics of Mathematical Analysis and Linear Algebra.

In theoretical-practical lessons the expository and inquisitive method is used for 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 and they use the excel and statistical software (SPSS) in statistical analysis. In addition, students will be supervised, through
the clarification of theoretical doubts and exercises resolution.

Objectives:Learn, understand and know how to use basic probability and statistical tools that allow the students
exploring data and to analyze random models often used by practicing engineers.
Generic skills:Application of knowledge and understanding.Critical thinking. Interpretation of results.Accomplishment and decision making.Communication. Self-learning. Ability to work in groups,
developing interpersonal relationships.
Specific skills:To learn exploring data with graphs and numerical summaries;to learn the meaning of correlation
and how to obtain the equation of the least squares line, understanding the meaning of the regression
coefficients.To formalize problems involving the result of random experiments and identify the convenient
probabilistic models parameters. To know how to use data from an experiment to make inferences about population parameters. To know how to use statistical software (SPSS) in descriptive statistics, correlation and regression, and confidence intervals.

1.1. Methods of Collecting and Presenting Data. Exploring Data with graphs and numerical summaries.
Measures of position and measures of dispersion.
1.2 Association: Contingency, Correlation and Regression. Straight – line regression equations.
2. Probability and Common Probability Distributions.
Probability of an event. Applying the Probability Rules. Conditional Probability and independent events.
Probability Distributions. Probability distribution of a discrete random variable and probability distribution of a
continuous random variable.
Some special probability distributions.
3. Statistical Inference: Confidence Intervals.
Sampling distribution. Point and interval estimates of population parameters. Confidence Intervals.

NAO