Universidad Carlos III de Madrid
Iowa State Course Substitution
International Credits: 6.0
Converted Credits: 3.5
The main goal of the course is to provide the students with a set of competences for the understanding and application of statistical concepts and techniques in computer sciences. These competences can be classified as basic, general and specific. Basic competences: -Ability to gather and interpret relevant data (usually within their field of study) to inform judgments that include reflection on relevant social, scientific or ethical topics. (CB3) General competences: -Ability to apply knowledge of mathematics, statistics, computer science, and engineering as it applies to the fields of computer hardware and software. (PO a) -Ability to interpret data and results of experiments. (PO b) -Ability to independently acquire and apply required information related to statistical techniques with the aim of designing, monitoring, and managing computer systems. (PO i) -Ability to communicate effectively by oral, written, and graphical means, the results of statistical analysis. (PO g) -Ability to solve mathematical problems arising in engineering. Ability to apply knowledge of linear algebra; differential and integral calculus; numerical methods; numerical algorithms; statistics and optimization. (CGB1) Specific competences: -Ability to analyze and sintetize the main information content in a set of univariate and multivariate data. -Ability to compute probabilities and statistical moments at different dimensions -Ability to use random variables as a statistical device to model real phenomena. -Ability to identify the appropriate probability model for specific real situations. -Knowledge of the properties of point and interval estimation methods, with the aim of doing statistical inference. -An ability to use statistical models as well as the ability to perform an optimal estimation of the parameters by maximizing the likelihood and minimizing the prediction errors.. -Ability to formulate and testing hypothesis about a population. -Ability to design lineal models that help to understand and predict real phenomena. -Ability to use statistical software.
- Evaluation Date:
- February 27, 2017
- Amy Froelich
Course covers almost all components of STAT 305. Textbooks are from Engineering Statistics, which should give students ample examples from the field.