ECTS credits ECTS credits: 4.5
ECTS Hours Rules/Memories Hours of tutorials: 2.25 Expository Class: 18 Interactive Classroom: 18 Total: 38.25
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 Nursing
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
To provide students with the statistical techniques that are essential in experimentation in Health Sciences in general, and in Nursing in particular. To train students in data analysis and statistical reasoning. To learn how to use statistical software to solve statistical problems.
STATISTICS (18 hours of lectures, 10 hours of seminars and 8 hours of practical work in the Computer Room).
Topic 1. Descriptive statistics.
1.1 General concepts.
1.2 Frequency distributions.
1.3 Graphical representations.
1.4 Characteristic measures: position, dispersion and shape.
1.5 Descriptive statistics for two variables. Linear regression.
Topic 2. Probability.
2.1 Basic concepts of probability.
2.2 Conditional probability and independence.
Topic 3. Random variables.
3.1 Concept of random variable.
3.2 Discrete random variables.
3.3 Continuous random variables.
Topic 4. Introduction to statistical inference.
4.1 Introduction to statistical inference.
4.2 Sampling methods.
4.3 Sampling distributions in normal populations.
4.4 Parameter estimation: point estimation and estimation by intervals.
Topic 5. Hypothesis testing.
5.1 Introduction to hypothesis testing.
5.2 Hypothesis testing procedure.
5.3 One-population and two-population tests.
5.4 Hypothesis testing in the simple linear regression model.
5.5 Independence and normality tests.
Computer classroom practicals
Practical 1. Introduction to SPSS. Descriptive statistics.
Practice 2. Hypothesis testing.
Practice 3. Bivariate analysis and regression with SPSS.
Practice 4. Introduction to R
The study materials for the subject will be available on the virtual campus, in which the theoretical contents, illustrative examples, exercise bulletins for the seminars and computer practice scripts will be developed.
BASIC BIBLIOGRAPHY
Crujeiras, R.M. and Faraldo, P. (2010): "Manual de estadística básica para ciencias de la salud", Unidixital
Rius Díaz, F. and Wärnerberg Wärnerberg, Julia (2014): Bioestadística. Paraninfo.
COMPLEMENTARY BIBLIOGRAPHY
Alonso-Pena, M.; Bolón, D.; Ameijeiras-Alonso, J.; Saavedra-Nieves, A.; Saavedra-Nieves, P. (2023). "Manual de R para prácticas de Bioestadística", Universidade de Santiago de Compostela, Santiago de Compostela.
Martínez González, M.A.; Sánchez Villegas, A.; Toledo Atucha , E.; Faulin Fajardo, J. (2020): "Bioestadística amigable", Elsevier.
Montanero Fernández, J.; Minuesa Abril, C. (2018): "Estadística básica para Ciencias de la salud". Available at:
http://matematicas.unex.es/~jmf/Archivos/Manual%20de%20Bioestadística.p… [Accessed May 12, 2024]
Milton J.S. (2007) Estatística para Bioloxía e Ciencias da Saúde. Interamericana- McGraw- Hill (3ª edición).
Rosner, B. (2011) “ Fundamentals of Bioestatistics”. Wadsworth Publishing Company. Duxbury Press (5ª edición).
Verzani, J. (2002): "simpleR. Using R for Introductory Statistics". Available at:
https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf [Accessed May 12, 2024]
Within this subject, the aim is to contribute to the students achieving the competences set out in the USC Bachelor's Degree in Nursing:
Basic:
CB1. That students have demonstrated to possess and understand knowledge in an area of study that starts from the basis of general secondary education, and is usually at a level that, although it is supported by advanced textbooks, also includes some aspects that involve knowledge from the forefront of their field of study.
CB2. Students are able to apply their knowledge to their work or vocation in a professional manner and possess the competences usually demonstrated through the development and defence of arguments and problem solving within their field of study.
CB3. Students have the ability to gather and interpret relevant data (usually within their area of study) in order to make judgements that include reflection on relevant social, scientific or ethical issues.
CB4. Students are able to transmit information, ideas, problems and solutions to both specialist and non-specialist audiences.
CB5. That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy.
General:
CG3. Know and apply the theoretical and methodological foundations and principles of nursing.
CG6. Base nursing interventions on scientific evidence and available resources.
CG14. Establish assessment mechanisms, considering scientific-technical and quality aspects.
Transversal:
CT1. Ability to apply knowledge to practice.
CT5. Ability to solve problems.
CT7. Capacity for analysis and synthesis.
CT9. Decision-making skills.
CT14. Information management skills (ability to search for and analyse information from different sources).
CT16. Research skills.
CT17. Basic computer skills.
Specific:
CE6.Apply health care information and communication technologies and systems.
In the expository teaching sessions, the theoretical and practical concepts of the contents will be explained, supported by multimedia presentations. Some typical problems will also be solved, so that students can work on the exercise sheets that will be provided. In addition to the recommended bibliography, students will be provided with complementary teaching material. The interactive laboratory classes will take place in the computer room where students will be introduced to the use of statistical packages. In this session, students will also work on the clinical cases shared with other subjects of the course. In order to follow the practical classes, students will be provided with the syllabus. The other part of the interactive teaching will take place in the classroom and will be aimed at problem solving.
The tutorials are designed to monitor student learning.
Continuous assessment (20%): continuous assessment includes several tests throughout the course, including the resolution and delivery of practical cases proposed by the teacher. In order to be assessed, students must attend at least 75% of the interactive sessions. This qualification is retained between sessions of the same academic year.
Virtual course on Training in Information Competences in Nursing (10%).
Final exam (70%): the final exam will consist of several theoretical-practical questions on the contents of the subject, which may include the interpretation of results obtained with the statistical package used in the interactive teaching.
The weight of the continuous assessment in the extraordinary opportunity of recovery (July tests) will be the same (30%).
For cases of fraudulent performance of exercises or tests, the "Regulations for the evaluation of students' academic performance and revision of grades" will be applicable.
In this subject, students have 36 hours of classroom teaching (18 hours of lectures and 18 hours of interactive teaching). For each hour of expository teaching, it is considered necessary to dedicate around 1.5 hours of student work to study (revision of concepts and consultation of bibliography).
In relation to interactive teaching, for each hour, one hour is considered necessary for revision of the class. In addition, students should bear in mind that it is necessary to practice problem solving (from the bulletins or the recommended bibliography).
Attendance at the lectures and interactive sessions is essential to follow and pass the subject. Students must complete all the activities recommended by the lecturers (problem solving, literature review and practical exercises) in order to successfully pass the subject.
The students will have the materials of the course in the Virtual Campus (Moodle). In these materials are the contents (theoretical and practical) of the subject.
Pedro Faraldo Roca
Coordinador/a- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- Phone
- 881813216
- pedro.faraldo [at] usc.es
- Category
- Professor: University Lecturer
Jose Ameijeiras Alonso
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- jose.ameijeiras [at] usc.es
- Category
- Professor: LOU (Organic Law for Universities) PhD Assistant Professor
| Monday | |||
|---|---|---|---|
| 09:00-10:00 | Grupo /CLE_02 | Spanish | Classroom 3.01 |
| 10:00-11:00 | Grupo /CLE_01 | Spanish | Classroom 2.03 |
| 16:00-18:00 | Grupo /CLIS_01 | Spanish | Classroom 3.01 |
| 18:00-20:00 | Grupo /CLIS_02 | Spanish | Classroom 3.01 |
| Tuesday | |||
| 09:00-10:00 | Grupo /CLE_02 | Spanish | Classroom 3.01 |
| 10:00-11:00 | Grupo /CLE_01 | Spanish | Classroom 2.03 |
| 16:00-18:00 | Grupo /CLIS_03 | Spanish | Classroom 3.01 |
| 18:00-20:00 | Grupo /CLIS_04 | Spanish | Classroom 3.01 |
| Wednesday | |||
| 09:00-10:00 | Grupo /CLE_02 | Spanish | Classroom 3.01 |
| 10:00-11:00 | Grupo /CLE_01 | Spanish | Classroom 2.03 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_01 | Classroom 2.01 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_02 | Classroom 2.01 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_02 | Classroom 2.03 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_01 | Classroom 2.03 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_01 | Classroom 3.01 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_02 | Classroom 3.01 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_02 | Classroom 3.02 |
| 12.16.2024 16:00-18:00 | Grupo /CLE_01 | Classroom 3.02 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_01 | Classroom 2.01 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_02 | Classroom 2.01 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_02 | Classroom 2.02 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_01 | Classroom 2.02 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_01 | Classroom 2.03 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_02 | Classroom 2.03 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_01 | Classroom 3.01 |
| 06.25.2025 10:00-12:00 | Grupo /CLE_02 | Classroom 3.01 |