| Study programme competencies |
| Code | Study programme competences |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| Capacity for abstraction, understanding, analysis and simplification of instances and processes. | A1 |
B2 B3 B4 B5 B6 B7 |
C1 C4 |
| Using statistical software for solving engineering problems involving randomness and large volume of data. | A1 |
C1 |
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| Ability to solve statistical problems encountered in engineering. | A1 |
C1 |
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| Contents |
| Topic | Sub-topic |
| Introduction to Statistics | |
| 2. Exploratory data analysis. | |
| 3. Probability. | |
| 4. Ramdom variables. | |
| 5. Discrete random variables and probability distributions. | |
| 6. Continous random variables and probability distributions. | |
| 7. Joint probability distributions. | |
| 8. Statistical inference. | |
| 9. Point estimation of parameters. | |
| 10. Statistical intervals for a single sample. | |
| 11. Test of hypotheses for a single sample. | |
| 12. Regression an analysis of variance (ANOVA). |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A1 B2 B6 B7 | 30 | 36 | 66 |
| Problem solving | A1 B3 B4 B5 C1 C4 | 20 | 18 | 38 |
| ICT practicals | A1 B6 B7 C1 C4 | 10 | 10 | 20 |
| Mixed objective/subjective test | A1 B2 B3 B4 B5 | 3 | 9 | 12 |
| Objective test | A1 B2 B3 B4 | 3 | 9 | 12 |
| Personalized attention | 2 | 0 | 2 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Guest lecture / keynote speech | Lectures about the course topics. |
| Problem solving | Solving exercises and statistical problems encountered in engineering. |
| ICT practicals | Resolution of practical cases of statistical problems by Excel. |
| Mixed objective/subjective test | Midterm exam of the first issues of the subject. |
| Objective test | Final exam of the subject |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| ICT practicals | A1 B6 B7 C1 C4 | Evaluation of case studies solved in small groups. | 25 |
| Objective test | A1 B2 B3 B4 | Final exam with test questions and troubleshooting. | 50 |
| Mixed objective/subjective test | A1 B2 B3 B4 B5 | Midterm exam with test questions and troubleshooting. | 25 |
| Assessment comments | |||
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| Sources of information |
| Basic |
Douglas C. Montgomery, George C. Runger (2011). Applied Statistics and Probability for Engineers. John Wiley
García del Valle, Alejandro; Crespo, Diego (2010). Apuntes de Estadística para Ingenieros. Moodle UDC |
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| Complementary |
S. Christian Albright, Wayne Winston, Christopher J. Zappe (1999). Data Analysis & Decision Making with Microsoft Excel. Duxbury
Ronald E. Warpole (1999). Probabilidad y Estadística para Ingenieros. Pearson |
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| Recommendations | ||
| Subjects that it is recommended to have taken before |
| Subjects that are recommended to be taken simultaneously |
| Subjects that continue the syllabus | ||
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| Other comments | |
| <p> .</p> |