ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Student's work ECTS: 99 Hours of tutorials: 3 Expository Class: 24 Interactive Classroom: 24 Total: 150
Use languages Spanish, Galician, English
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Center Faculty of Mathematics
Call: First Semester
Teaching: Sin Docencia (En Extinción)
Enrolment: No Matriculable (Sólo Planes en Extinción)
To introduce the students in the tools of the Descriptive Data Analysis and the Theory of Probability. To learn introductory R language fundamentals and basic syntax for introductory statistics.
Descriptive statistics for one variable (5 lecture hours).
Introduction to descriptive statistics. Types of data and variables.
Frequencies. Measures of location, dispersion and shape.
Graphic tools of descriptive analysis of one variable.
Two-dimensional descriptive statistics (4 lecture hours).
Joint distribution of frequencies. Tables. Marginal and conditional frequencies.
Graphic tools for two variables.
Linear dependence. Regression lines. Covariance and correlation.
Probability Calculus (7 lecture hours).
Probability space. Events. Probability. Properties.
Conditional probability. Independence. Law of total probability. Bayes' theorem.
Combinatorics
One-dimensional random variables (5 lecture hours).
Random variable. Distribution function. Types of random variables: Discrete and continuous. Mass probability function and density function.
Characteristics of a random variable. Transformation of random variables.
Main models of probability (7 lecture hours).
Discrete: Uniform, Bernoulli, Binomial, Poisson, Hipergeometric, Geometric, Negative Binomial.
Continuous: Uniform, Normal, Exponential, Gamma, Beta.
Relations of interest between the distributions.
Contents of the laboratory classes (14 laboratory hours).
The statistica package R.
Exploratory data analysis.
Generation of probability models with R.
Basic bibliography:
- FREEDMAN, D. et al.(2011). Statistics. Fourth edition. Viva Books. (2nd edition in spanish: Estadística. Antoni Bosch, 1993).
- PEÑA, D. (2008). Fundamentos de Estadística. Segunda edición. Ciencias Sociales Alianza Editorial.
- TIJMS, H. C. (2016). Understanding Probability. Third edition. Cambridge University Press.
Complementary bibliography:
- CAO, R. et al. (2006). Introducción a la Estadística y sus aplicaciones. Ciencia y técnica (Pirámide).
- GONICK, L., SMITH, W. (2001). Á Estadística ¡en caricaturas!. Published by SGAPEIO.
- GRINSTEAD, C. M., SNELL, J. L. (1997). Introduction to Probability. Second edition. AMS.
- ROHATGI, V. K., EHSANES SALEH, A. K. Md. (2015) An Introduction to Probability and Statistics. Wiley Online Library. (Available online through the University Library).
- VERZANI, J. (2005). Using R for Introductory Statistics. Chapman and Hall.
According to the document "Memoria do Grao en Matemáticas da USC", competences that should be acquired across this course are:
Basic competencies: CB1-CB5
General competencies: CG1-CG5
Transversal competencies: CT1-CT5
Specific competencies: CE1-CE9
IMPORTANT NOTE: Starting from the 2025-2026 academic year, this subject will be considered discontinued, and enrolled students will no longer have the right to teaching. They will only have the right to take the exam, which will be conducted according to the contents established in this syllabus.
Although no face-to-face or virtual classes will be provided, students may request tutorials to address doubts related to the preparation for the final exam. These tutorials may take place either in person or online via MS Teams, upon prior request to the lecturer.
IMPORTANT NOTE: Starting from the 2025-2026 academic year, this subject will be considered discontinued, and enrolled students will no longer have the right to teaching. They will only have the right to take the exam, which will be conducted according to the contents established in this syllabus.
The student must take a final written exam, which will be held in person and will account for 100% of the final grade. These conditions will apply both to the first and second examination opportunities.
The final exam will consist of a section with short questions aimed at assessing the acquisition of key knowledge of the subject. The rest of the exam will consist of solving exercises and problems related to the contents of the subject, including a specific section to evaluate the understanding of the R software, its syntax, and the interpretation of code within the context of the subject matter.
Students who do not attend the final exam will be considered as "Not Presented."
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The free software R can be downloaded at the following link: http://www.r-project.org/.
Important warning: In case of fraudulent conduct during the exam (plagiarism or improper use of technology), the regulations on student academic performance assessment and grade review will apply.
Beatriz Pateiro Lopez
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- Phone
- 881813185
- Category
- Professor: University Lecturer
| 12.18.2025 10:00-14:00 | Grupo de examen | Classroom 06 |
| 06.17.2026 10:00-14:00 | Grupo de examen | Classroom 06 |