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Educational guide | |||||||||||||||||||||||||||||||||||||||
| IDENTIFYING DATA | 2024_25 | |||||||||||||||||||||||||||||||||||||||
| Subject | STATISTICS | Code | 00208007 | |||||||||||||||||||||||||||||||||||||
| Study programme |
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| Descriptors | Credit. | Type | Year | Period | ||||||||||||||||||||||||||||||||||||
| 6 | Basic Training | First | Second |
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| Language |
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| Prerequisites | ||||||||||||||||||||||||||||||||||||||||
| Department | MATEMATICAS |
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| Coordinador |
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aquic@unileon.es |
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| Lecturers |
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| Web | http:// | |||||||||||||||||||||||||||||||||||||||
| General description | Statistics is a subjet of basic instruction, necessary in the analysis and verification of experimental data. It combines theoretical classroom training, and practice software | |||||||||||||||||||||||||||||||||||||||
| Tribunales de Revisión |
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| Competencias |
| Code | |
| A14019 | |
| A14020 | |
| A14021 | |
| A14022 | |
| A14023 | |
| A14068 | |
| A14089 | |
| A14090 | |
| A14092 | |
| A14096 | |
| A14099 | |
| A14101 | |
| C1 | CMECES1 That students have demonstrated possession and understanding of knowledge in an area of study that is based on general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that involve knowledge from the cutting edge of their field of study |
| C2 | CMECES2 That students know how to apply their knowledge to their work or vocation in a professional manner and possess the skills that are usually demonstrated through the development and defense of arguments and the resolution of problems within their area of study. |
| C3 | CMECES3 That students have the ability to gather and interpret relevant data (normally within their area of study) to make judgments that include reflection on relevant issues of a social, scientific or ethical nature. |
| C4 | CMECES4 That students can transmit information, ideas, problems and solutions to both a specialised and non-specialised audience |
| C5 | CMECES5 That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy |
| Learning aims |
| Competences | |||
| Distinguishing problems that can be solved with probability and statistics | A14019 A14020 A14089 A14090 A14096 A14099 |
C1 C2 |
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| Designing studies to solve problems in their discipline | A14020 A14021 A14022 A14090 A14092 A14096 A14099 |
C2 C3 C4 |
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| Analysing data from their discipline, interpreting and presenting the results appropriately, being able to compare and discuss them, where appropriate, with other published work and results | A14020 A14021 A14022 A14089 A14090 A14092 A14096 A14099 A14101 |
C2 C3 C4 |
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| Acquiring the basic knowledge of probability and statistics, so that they are able to undertake further studies or read advanced content with autonomy | A14019 A14021 A14023 A14096 |
C1 C3 C5 |
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| Using computer applications to solve problems related to statistical computing | A14068 A14099 |
C5 |
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| Contents |
| Topic | Sub-topic |
| Topic I: Probability | 1. Probability 2. Random variables 3. Distribution models |
| Topic II: Statistics | 1. Considerations on study design 2. Descriptive statistics and exploratory data analysis 3. Inference 4. Regression and introduction to multivariate analysis |
| Planning |
| Methodologies :: Tests | |||||||||
| Class hours | Hours outside the classroom | Total hours | |||||||
| Problem solving, classroom exercises | 20 | 33 | 53 | ||||||
| Practicals using information and communication technologies (ICTs) in computer rooms | 10 | 15 | 25 | ||||||
| Tutorship of group | 6 | 11 | 17 | ||||||
| Lecture | 18 | 27 | 45 | ||||||
| Objective multiple-choice tests | 4 | 0 | 4 | ||||||
| Mixed tests | 6 | 0 | 6 | ||||||
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | |||||||||
| Methodologies |
| Description | |
| Problem solving, classroom exercises | Problem posing and solving in the classroom. |
| Practicals using information and communication technologies (ICTs) in computer rooms | Solving exercises with a computer. |
| Tutorship of group | Monitoring of the student's learning process. Content review and problem-solving sessions will be held. |
| Lecture | Theoretical presentations in which the lecturer introduces the concepts, results and methods of the discipline. |
| Personalized attention |
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| Assessment |
| Description | Qualification | ||
| Mixed tests | Two partial written exams | 38%, 42% | |
| Objective multiple-choice tests | On-line assessment tests | 20% | |
| Other comments and second call | |||
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In order to pass the course in the first call (ordinary call), by continuous assessment, it will be necessary to achieve a minimum mark of 20 points in both mid-term exams, including the mark for the online tests, and the final mark must be higher than 50 (out of 100). Students who do not pass the first exam will have to sit the second call (extraordinary exam), which will consist of a single written exam with content from both parts. |
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| Sources of information |
| Access to Recommended Bibliography in the Catalog ULE |
| Basic |
Verzani, J., Using R for introductory statistics, Chapman and Hall, 2005
Bertsekas, D.P. & Tsitsiklis, J., Introduction to probability, Athena Scientific, 2008
Agresti, A.; Klingenberg, B.; Franklin, C. & Posner, M., Statistics : the art and science of learning from data, Pearson, 2018 |
https://catoute.unileon.es/permalink/34BUC_ULE/4ifthk/alma991008829177805772 https://catoute.unileon.es/permalink/34BUC_ULE/4ifthk/alma991008847377605772 |
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| Complementary |
Everitt, B.S. & Hothorn, T., A Handbook of Statistical Analyses Using R, CRC Press, 2009
Milton, J.S., Estadística para biología y ciencias de la salud, McGraw-Hill , 2007
Quinn, G.P. & Keough, M.J., Experimental design and data analysis for biologists, Cambridge, 2002
Devore, J.L., Probabilidad y estadística para ingeniería y ciencias, Cengage Learning, 2016 |
| Recommendations |
| Subjects that it is recommended to have taken before | ||
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