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Credits  Dept.  Type  Requirements 

9.0 (7.2 ECTS)  EIO 

AL
 Prerequisite for DIE , DCSYS , DCSFW CAL  Prerequisite for DIE , DCSYS , DCSFW 
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This subject introduces techniques for data analysis (descriptive statistics...), which allow students to take on the challenge of interpreting the sorts of data they will encounter in the professional world. The subject also introduces basic aspects of applied probability, which computer scientists may need over the course of their professional careers. These basics lay the foundations for working in the following areas: system and/or software reliability, the study of system performance, the processing of simulation and queue theory data, the design of quantitative information systems and the statistical exploitation of databases, et cetera.
Estimated time (hours):
T  P  L  Alt  Ext. L  Stu  A. time 
Theory  Problems  Laboratory  Other activities  External Laboratory  Study  Additional time 

T  P  L  Alt  Ext. L  Stu  A. time  Total  

0  0  8,0  0  8,0  0  0  16,0  


T  P  L  Alt  Ext. L  Stu  A. time  Total  

4,0  2,0  0  0  0  6,0  0  12,0 

T  P  L  Alt  Ext. L  Stu  A. time  Total  

14,0  4,0  0  0  0  22,0  0  40,0  
Probability distribution models.


T  P  L  Alt  Ext. L  Stu  A. time  Total  

12,0  4,0  4,0  0  4,0  16,0  0  40,0  
Sampling, statistical inference, estimation, testing hypotheses.


T  P  L  Alt  Ext. L  Stu  A. time  Total  

10,0  6,0  6,0  0  6,0  16,0  2,0  46,0  
Linear model, ANOVA.


T  P  L  Alt  Ext. L  Stu  A. time  Total  

4,0  0  4,0  0  4,0  4,0  0  16,0  
Introduction to simulation. Applications to queuing models.

Total per kind  T  P  L  Alt  Ext. L  Stu  A. time  Total 
44,0  16,0  22,0  0  22,0  64,0  2,0  170,0  
Avaluation additional hours  10,0  
Total work hours for student  180,0 
Lectures illustrated with slides and whiteboard notes. These methods may be replaced with a computer and LCD projector, facilitating the use of ICT (e.g. software demonstrations, the use of applets, Internet access, etc.).
Students will tackle problems on a cooperative basis. For example, a group of students will work on a problem for which the preparatory work has been done by other groups. Exercises will also be carried out on computers providing selfcorrection in a socalled estatus environment. The teacher may occasionally explain and solve exercises for illustration purposes.
In the lab, students will work in groups with their respective computers, following work guidelines covering the session in question.
The teacher will be on hand to provide guidance and to answer questions.
Students will read the guidelines before each session. Students may also be required to finish off work after the session and complete a questionnaire.
The final grade will be made up as follows:
 (20%) a partial grade corresponding to some problems or multiplechoice test during the term and held in class time (between three and five)
 (20%) a lab grade corresponding to a maximum of six weigthed tests carried out during the term
 (60%) a final exam
If the final exam grade is higher than the grade obtained using the previous weigths, the course grade awarded will be that obtained in the final exam.
Students must have sufficient knowledge of algebra and mathematical analysis in order to assimilate concepts regarding set algebra, numerical series, the functions of real variables in one or more dimensions, derivation and integration.