ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Hours of tutorials: 3 Expository Class: 27 Interactive Classroom: 21 Total: 51
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Statistics, Mathematical Analysis and Optimisation
Areas: Statistics and Operations Research
Center Faculty of Biology
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
Purchase the handle, under a practical approach, of the diverse technicians that allow a correct and rigorous approach, collected, analysis and interpretation of data especially focused to the field of the Biotechnology.
These aims centre in the foundations and basic models of the statistical methods and in the exploratory and inference analysis of the data.
- Know obtain, organise, present and describe groups of data by means of descriptive statistics.
- Know calculate the probability of an event.
- Know the characteristics and distribution of the random variables.
- Know describe and apply methods of statistical inference.
- Know describe and apply mathematical models of linear regression and analysis of the variance.
Lectures (27 hours)
Chapter 1. Descriptive statistics (5 hours)
Chapter 2. Probability (3 hours)
Chapter 3. Random variables (4 hours)
SubChapterject 4. Introduction to the statistical inference: punctual estimate, intervals of confidence and contrasts of hypothesis. Inference in normal populations (8 hours)
Chapter 5. Linear regression (4 hours)
Chapter 6. Analysis of the variance (3 hours)
Seminars (11 hours)
- Resolution of the exercises proposed in each chapter.
Computer Labs (10 hours)
- Implementation of the methods with the statistical software R.
Basic Bibliography:
Milton, J.S., 2007. Estadística para biología y ciencias de la salud. 3ª ed. amp. Madrid: Mc Graw-Hill Interamericana.
Verzani, J., 2005. Using R for Introductory Statistics. Boca Raton, FL: Chapman and Hall/CRC. Disponible en línea: <https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf>
Complementary Bibliography:
Dalgaard, P., 2008. Introductory statistics with R. 2nd ed. New York: Springer.
Daniel, W.W., 2009. Biostatistics: basic concepts and methodology for the health sciences. 9th ed. Hoboken, NJ: John Wiley & Sons.
Peña, D., 2005. Fundamentos de estadística. Madrid: Alianza.
Rosner, B., 2011. Fundamentals of biostatistics. 7th ed. Boston: Brooks/Cole.
Rius Díaz, F. and Wärnberg, J., 2014. Bioestadística. 2ª ed. Madrid: Paraninfo.
Within the learning results that are included in the Biotechnology Degree Verification Report, this subject will address the following knowledge/content, abilities/skills and competencies:
Knowledge/content:
- Con01: know the most important concepts, methods and results of the different branches of Biotechnology.
Skills/Abilities:
- H/D02: search, process, analyze/interpret and synthesize relevant information and results from various sources and obtain conclusions on topics related to Biotechnology.
- H/D04: interpret experimental results and identify consistent and inconsistent elements.
- H/D06: maintain an ethical commitment, as well as a commitment to equality and integration.
- H/D10: knowing how to analyze data and interpret experimental results typical of the fields of Biotechnology.
Competencies:
- Comp01: 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 topics of a social, scientific or ethical nature.
- Comp02: that students are able, both in writing and orally, to debate and transmit information, ideas, problems and solutions related to Biotechnology to both a specialized and non-specialized/general public.
- Comp04: that students know how to apply the theoretical-practical knowledge acquired in the degree in a professional manner and are competent in posing/solving problems, as well as in developing/defending arguments in both related academic and professional contexts. with innovation and the biotechnology industry.
- Comp05: Study and learn autonomously, with organization of time and resources, new knowledge and techniques in Biotechnology and acquire the ability to work as a team.
- The matter has six credits ECTS delivered in 27 hours of lectures, 11 hours of interactive teaching and 10 hours of computer. labs
- The classes will develop in the classroom assigned doing use fundamentally of the blackboard and of presentations. It will boost the participation of the students in the classes, especially in the most practical appearances. Also they will argue and they will resolve diverse exercises billed in bulletins, that will be available to students in the Campus Virtual, to boost his personal work, using also to evaluate his use.
- The students will have the support of the Campus Virtual of the USC, through the page of the course, to have of access to the programs, bibliography and distinct bulletins of exercises, as well as to notes of some subjects and information on voluntary complementary activities and tools of communication.
Continuous assessment (30%): the continuous assessment will carry out along the semester. It will consist of the following elements:
-Resolution of exercises of the bulletins associated to each chapter and exhibition in the seminars.
-Delivery of exercises resolved and properly drafted for his evaluation by the profesorado.
-Intermediate test that will include different theoretical-practical questions about the contents of the subject.
-Evaluation forms of the computer labs, that willperform in the own hours of interative teaching.
By means of this activity evaluate the following learning results: Con01, H/D02, H/D04, H/D06, H/D10, Comp01, Comp02, Comp04 and Comp05. Moreover, the qualification obtained by continuous assessment will be conserved only for the second call of the same course.
Final exam (70%): the final exam will consist of several theoretical and practical questions about the contents of the matter, inside which will be able to include the interpretation of results obtained with the statistical software used in the computer labs. By means of this activity evaluate the following learning results: Con01, H/D10, Comp04 and Comp05.
The repeater students will have the same assessment system. It considers that one student has presented to an announcement when he/she has participated in assessment activities evaluation that suppose more than 50% of the total assessment. Furthermore, the assessment system will be the same in the second evaluation opportunity.
For the cases of fraudulent realisation of exercises or proofs will be of application the collected in the "Normativa de evaluación del rendimiento académico de los estudiantes y de revisión de calificaciones".
In this subject, the student must attend 48 hours of lectures (27 lectures and 21 interactive). For each lecture hour, about 1.5 hours is considered necessary for the revision of concepts and bibliography consulting.
For the interactive part, one hour of self-study for each session hour would be enough for revising the class work. Apart from this work, the students must be aware of the importance of being able to solve problems (from the exercise assigments or from the recommended bibliography).
- Assistance to all the educational activities and follow-up of the tasks proposed by the professors of the subject.
- Do use of the samll groups to consult any doubt that can arise.
- Devote to the study of the subject a regularly distributed time along the quarter.
The teaching material will be made available to students through the USC Virtual Campus.In addition, the software used in the interactive laboratory sessions can be downloaded for free at the following link https://cran.r-project.org/
Maria Angeles Fernandez Sotelo
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- Phone
- 881813210
- mangeles.fernandez.sotelo [at] usc.es
- Category
- Professor: University Lecturer
Mercedes Conde Amboage
Coordinador/a- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- mercedes.amboage [at] usc.es
- Category
- Professor: Temporary PhD professor
Maria Vidal Garcia
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- mariavidal.garcia [at] usc.es
- Category
- Ministry Pre-doctoral Contract
| Monday | |||
|---|---|---|---|
| 13:00-14:00 | Grupo /CLE_01 | Spanish, Galician | Classroom 01. Charles Darwin |
| Tuesday | |||
| 13:00-14:00 | Grupo /CLE_01 | Galician, Spanish | Classroom 01. Charles Darwin |
| 12.20.2024 16:00-20:00 | Grupo /CLE_01 | Classroom 04: James Watson and Francis Crick |
| 06.16.2025 16:00-20:00 | Grupo /CLE_01 | Classroom 03. Carl Linnaeus |