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
Departments: Statistics, Mathematical Analysis and Optimisation
Areas: Statistics and Operations Research
Center Faculty of Mathematics
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
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 (4 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 (5 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. This book can be downloaded from http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probabili…
- 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
Lectures will consist, basically, in lessons given by the lecturer dedicated to the exposition of theoretical contents and the resolution of problems or exercises. Competences that should be acquired across this lectures are: CB1-CB4, CG1-CG4, CT3, CT5, CE1-CE7.
During the problem sessions, students will develop their capacity to solve exercises related to the concepts described in the theory classes. Competences that should be acquired across this sessions are: CB1-CB4, CG1-CG4, CT1-CT5, CE1-CE7.
The lab sessions will serve for the acquisition of practical skills and the illustration of theoretical contents. Competences that should be acquired across this sessions are: CB1-CB4, CG1-CG4, CT1-CT5, CE1-CE9.
In preparing the final exam and the partial evaluations, students will develop competences CB1-CB5, CG1-CG5, CT1-CT5, CE1-CE7.
All the tasks of the student will be oriented by the teacher in the tutorial sessions.
The material for this course will be available through the Virtual campus of the USC. Also, communications with the students will be carried out through this platform. The material for this course will be available through the Virtual campus of the USC. Also, communications with the students will be carried out through this platform. MS Teams will be used as a synchronous communication tool. Depending on the healthcare scenario in which the teaching will be develope, the methodology will be adapted as follows:
SCENARIO 1 (adapted normality):
The expository and interactive teaching will be on classroom, according to the distribution organized by the Faculty of Mathematics, using the virtual course as support, in which the students will find bibliographic and teaching materials, together with problem bulletins. The tutorials will be in person, via email or through MS Teams.
SCENARIO 2 (distancing):
Partially virtual teaching, according to the distribution organized by the Faculty of Mathematics. For this the virtual classroom of the course will be used, with explanatory videos and bibliographic materials provided by the teacher.
The tutorials will be attended by email or through MS Teams.
SCENARIO 3 (closing of the faculty):
During the suspension of the presential activity, the following teaching methodology will be used:
1) Preparation of generic material (notes and video notes) and specific teaching material for this situation (solved exercises, links to content presentations, support material) that will be uploaded to the virtual classroom periodically.
2) Weekly planning of the contents to be developed.
3) Proposal of activities and/or exercises to solve, and send.
4) Creation of a forum for debate and doubts in the virtual classroom. Both students and teachers can participate in this forum. Both to formulate questions and to solve them.
5) Use of the MS Teams software to support face-to-face activities, which will preferably take place during the already scheduled school hours. Tutoring groups will be created, which will allow the interactive resolution of doubts.
Scenario 1
The qualification will be done through continuous assessment, based on training activities, and final exam. The grade will be the maximum of the final exam grade and the weighting of this exam grade with continuous evaluation where the relative weight of each section will be 60% -40%, respectively
The continuous evaluation will consist of the resolution of problems and questions that will be scheduled periodically in the expository sessions / seminars, laboratory and will be carried out individually or in groups, always with the available class material. The Virtual Campus may be used if the conditions determined by the Faculty of Mathematics do not allow the simultaneous presence of all the students in a group. There will be a minimum of 4 sessions, two of seminar and two of laboratory, and a maximum of 5, three of seminar and two of laboratory. Each formative test will be evaluated between 0 and 10 and the teacher will comment on the tasks in the following sessions. The continuous assessment score will be the average of the three highest scores, necessarily including an expository / seminar test and a laboratory test.
The final exam will consist of a part based on short questions that is intended to assess the acquisition of key knowledge of the subject. The rest of the exam will consist of solving exercises and problems similar to those proposed throughout the course. The exam will include evaluation questions of the competences with R.
The evaluation of the competences will be carried out according to what is established in the methodology section.
SCENARIO 2 (distancing):
The same procedure as that described for SCENARIO 1. The tasks of the expository session/seminar will be exclusively in seminar and the Virtual Campus can also be used if the conditions determined by the Faculty of Mathematics do not allow the simultaneous presence of all the students in a group. Laboratory task will be delivered to the Virtual Campus. The final exam will be telematic.
SCENARIO 3 (closing of the faculty):
The same procedure as that described for SCENARIO 2. The continuous assessment tasks will be done through the Virtual Campus, with the support of MS Teams, during the Laboratory and Seminar hours. In this scenario, the tasks will be previously notified through the Virtual Campus.
In the second opportunity, the qualifications and criteria of continuous evaluation will be maintained, in the three scenarios.
Warning. In cases of fraudulent performance of exercises or tests (plagiarism or improper use of technologies), the provisions of the Regulations for the Evaluation of the Academic Performance of students and the revision of qualifications will apply.
The total number of working hours of the student is: 25 x 6 = 150. The distribution is as follows:
PRESENCE WORK IN THE CLASSROOM
Lectures classes: 26 hours
Solving-problems laboratory classes: 13 hours
Computer laboratory classes: 13 hours
Small groups tutorials: 2 hours
Total: 54 hours
HOURS OF PERSONAL WORK OF THE STUDENT
Individual and group self-study: 74 hours
Preparation of continuous assessment tests: 7 hours
Programming and other works with computer: 15 hours
Total: 96 hours
It is recommended to attend lectures and seminars and to do the suggested activities. It is also recommended the use of the R statistical package for exploring the practical usefulness of the techniques explained along the course.
Contingency plan:
Adaptation of the methodology to Scenarios 2 and 3:
SCENARIO 2 (distancing):
Partially virtual teaching, according to the distribution organized by the Faculty of Mathematics. For this, the virtual classroom of the course will be used, with explanatory videos and bibliographic materials provided by the teacher.
The tutorials will be attended by email and through MS Teams.
SCENARIO 3 (closure of the facilities):
The continuous assessment tasks will be done through the Virtual Campus, with the support of MS Teams, during the Laboratory and Seminar hours. In this scenario, the tasks will be previously notified through the Virtual Campus.
Adaptation of the evaluation system to Scenarios 2 and 3:
SCENARIO 2 (distancing):
Same procedure as that described for SCENARIO 1. The tasks of the exhibition / seminar session will be exclusively in seminar, and the Virtual Campus can be used for delivery if the sanitary conditions established by the Faculty of Mathematics do not allow the entire group to attend simultaneously. The laboratory tests will be delivered in the Virtual Campus. The final test will be telematic.
SCENARIO 3 (closure of the faculty):
Same procedure as described for SCENARIO 2. Continuous assessment tasks will be done through the Virtual Campus, with support from MS Teams, during Laboratory and Seminar hours. In this scenario, the tasks will be previously notified through the Virtual Campus.
In the second opportunity, the qualifications and criteria of continuous evaluation will be maintained, in the three scenarios.
Manuel Febrero Bande
Coordinador/a- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- Phone
- 881813187
- manuel.febrero [at] usc.es
- Category
- Professor: University Professor
Alberto Rodriguez Casal
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- alberto.rodriguez.casal [at] usc.es
- Category
- Professor: University Lecturer
Alejandra Maria Lopez Perez
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- alejandra.lopez.perez [at] rai.usc.es
- Category
- Ministry Pre-doctoral Contract
| Monday | |||
|---|---|---|---|
| 11:00-12:00 | Grupo /CLIS_04 | Spanish | Ramón María Aller Ulloa Main Hall |
| 12:00-13:00 | Grupo /CLIS_03 | Spanish | Classroom 06 |
| 12:00-13:00 | Grupo /CLE_01 | Spanish | Classroom 09 |
| Tuesday | |||
| 11:00-12:00 | Grupo /CLE_02 | Spanish | Classroom 08 |
| 12:00-13:00 | Grupo /CLE_01 | Spanish | Classroom 07 |
| Wednesday | |||
| 10:00-11:00 | Grupo /CLIL_03 | Spanish | Computer room 4 |
| 11:00-12:00 | Grupo /CLE_02 | Spanish | Classroom 08 |
| 11:00-12:00 | Grupo /CLIL_02 | Spanish | Computer room 2 |
| 13:00-14:00 | Grupo /CLIL_01 | Spanish | Computer room 3 |
| Thursday | |||
| 10:00-11:00 | Grupo /CLIL_06 | Spanish | Computer room 3 |
| 12:00-13:00 | Grupo /CLIS_02 | Spanish | Classroom 06 |
| 13:00-14:00 | Grupo /CLIS_01 | Spanish | Classroom 02 |
| 13:00-14:00 | Grupo /CLIL_05 | Spanish | Computer room 3 |
| Friday | |||
| 13:00-14:00 | Grupo /CLIL_04 | Spanish | Computer room 3 |
| 01.11.2021 16:00-20:00 | Grupo /CLE_01 | Classroom 02 |
| 01.11.2021 16:00-20:00 | Grupo /CLE_01 | Classroom 03 |
| 01.11.2021 16:00-20:00 | Grupo /CLE_01 | Classroom 06 |
| 01.11.2021 16:00-20:00 | Grupo /CLE_01 | Ramón María Aller Ulloa Main Hall |
| 07.01.2021 10:00-14:00 | Grupo /CLE_01 | Classroom 06 |