Educational guide School of Engineering |
english |
Bachelor's Degree in Computer engineering (2010) |
Subjects |
STATISTICS |
Learning outcomes |
IDENTIFYING DATA | 2023_24 |
Subject | STATISTICS | Code | 17234011 | |||||
Study programme |
|
Cycle | 1st | |||||
Descriptors | Credits | Type | Year | Period | ||||
6 | Basic Course | Second | 1Q |
Competences | Learning outcomes | Contents |
Planning | Methodologies | Personalized attention |
Assessment | Sources of information | Recommendations |
Type A | Code | Learning outcomes |
A2 |
Calculate the descriptive statistical parameters of a population. Use the most common probability distribution models to model real situations. Know the situations modelled by stochastic processes. Be able to analyse a situation from the point of view of statistical inference. Understand the descriptive statistical parameters of a population. | |
FB1 |
Understand binomial, normal, exponential and Poisson probability distributions. Use the most common probability distribution models to model real situations. Understand the fundamentals of queuing theory. Be able to apply the fundamentals of queuing theory to IT. Understand the basis of statistical inference. | |
Type B | Code | Learning outcomes |
B2 |
Master the central limit theorem. Use the stochastic process techniques in specific problems. Understand the fundamentals of queuing theory. Know the techniques of regression. | |
Type C | Code | Learning outcomes |