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
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Quantitative Economy
Areas: Quantitative Economics (USC-specific)
Center Faculty of Economics and Business Studies
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable
Statistical inference deals with techniques that are very useful in economics and business since it allows us to obtain valid conclusions about population behavior from sample data. Therefore, the basic objective of the subject is that the student may:
- Know and understand the concepts and methods of probability and statistical inference, and their application to the analysis of economic and business phenomena.
- Perform basic statistical analysis using computer tools.
- Be able to select and apply the most appropriate statistical techniques to the analysis of each phenomenon, and interpret the results obtained.
- Begin the analysis of empirical data of the economic and business reality (data collection, statistical analysis, model selection, interpretation and reliability of the results, etc.) and the formal presentation of the work carried out.
- Develop the capacities of understanding, reasoning, criticism and oral and written expression, by using an appropriate statistical-economic lexicon.
TOPIC 1 PROBABILITY
1.1 Theories of probability in statistics: classical, frequentist, subjective and axiomatic. Kolmogorov Axioms
1.2 Conditional and total probability.
1.3 Bayes' theorem
1.4 Independence of events.
TOPIC 2 PROBABILITY DISTRIBUTIONS
2.1 Random variables: discrete and continuous.
2.2 Probability distributions.
2.3 Characteristics associated with random variables. Mean, variance, moments.
2.4 Generalization to the two-dimensional and multidimensional case.
TOPIC 3 DISCRETE AND CONTINUOUS PROBABILITY MODELS
3.1 Binomial distribution.
3.2 Poisson distribution.
3.3 Univariate and bivariate Normal distribution.
3.4 Distributions derived from the Normal: Chi-square, t-Student, F-Snedecor.
TOPIC 4 INTRODUCTION TO STATISTICAL INFERENCE
4.1 Statistical Inference: populations and random samples.
4.2 Estimators.
4.3 Sample Distribution of the mean, variance and proportion.
TOPIC 5 ESTIMATOR
5.1 Estimation. Properties of point estimators
5.2 Point estimation methods: moment and maximum likelihood method.
5.3 Interval Estimation. Confidence interval construction methods. Confidence intervals in normal populations.
TOPIC 6 HYPOTHESIS TEST
6.1 Basic concepts: types of hypotheses, critical region and region of acceptance, types of errors, power of contrast.
6.2 Methodology of hypothesis testing.
6.3 Some parametric contrasts.
BASIC
Canavos, G.C. (1997). Probabilidad y Estadística. Aplicaciones y Métodos. Ed. McGraw Hill.
Fernández- Abascal, H., M. Guijarro, J.L. Rojo, J.A. Sanz. (1994): Cálculo de Probabilidades y Estadística. Ed. Ariel.
Lind, D.A.; Marchal, W.G. ; Wathen, S.A. (2015, 2012, 2008): Estadística Aplicada a los Negocios y a la Economía. Ed. McGrawHill.
Ruiz-Maya, L. (2004, 2002, 1999): Fundamentos de Inferencia Estadística. Ed. AC.
Esta materia contará con materiales elaborados por el profesorado, a disposición del alumnado en el CURSO VIRTUAL de la materia. http://www.usc.es/campusvirtual/
COMPLEMENTARY
Anderson, D. R.; Sweeney, D.J., Williams, T.A. (2001): Estadística para Administración y Economía. Vol.I. Thomson ed.
Berenson, M.L., Levine, D.M. (1996): Estadística Básica en Administración. Conceptos y Aplicaciones. Ed. Pearson Educación / Prentice Hall.
Casas Sánchez, J.M. (1996): Inferencia Estadística para Economía y Administración de Empresas. Ed. Centro de Estudios Ramón Areces.
Durá Peiró, J.M., López Cuñat, J.M. (1989): Fundamentos de Estadística. Estadística descriptiva y Modelos Probabilísticos para la Inferencia. Ed. Ariel.
Freund, J.E., Miller, I., Miller, M. (2000): Estadística matemática con aplicaciones. Ed. Pearson Educación / Prentice Hall.
García Barbancho, A. (1992): Estadística Teórica Básica. Probabilidad y modelos probabilísticos. Ed. Ariel.
Kazmier, L.J. (2006): Estadística aplicada a administración y economía. Ed. MnGraw Hil.
Martín Pliego, F.J., L. Ruiz-Maya. (1998): Fundamentos de Probabilidad. Ed. AC. (2ª edición, 2006)
Levin, R.I., Rubin, D.S. (1996): Estadística para administradores. Ed. Pearson Educación / Prentice Hall.
Newbold, P. (1998): Estadística para los negocios y la economía. Ed. Prentice Hall.
Newbold, P. ; Carlson, W.L.; Thorne, B. (2007): Estadística para administración y economía. Ed. Prentice Hall.
Novales Cinca, A. (1998): Estadística y Econometría. Ed. McGraw Hill.
Peña, D.; Romo, j. (1997): Introducción a la Estadística para las Ciencias Sociales. Ed. McGrawHill.
Ruiz-Maya, L., F.J. Martín Pliego. (1999): Fundamentos de Inferencia Estadística. Ed. AC. (2ª ed. 2000; 3ª ed.2005).
Sarabia Alegria, J.M. (2000): Curso práctico de estadística. Ed. Civitas.
Spiegel, M.R.; Schiller, J. ; Alu Srinivasan, R. (2010): Probabilidad y Estadística. Ed. McGraw-Hill.
Triola, M.F. (2004): Estadística. Ed. Pearson Educación.
Webster A.L. (1996): Estadística aplicada a la empresa y a la economía. Ed. Irwin.
PRACTICAL BOOKS
Baró Llinás, J. (1987): Cálculo de probabilidades. Ed. Parramón.
Baró Llinás, J. (1989): Inferencia estadística. Ed. Parramón.
Fernández- Abascal, H., M. Guijarro, J.L. Rojo e J.A. Sanz. (1995): Ejercicios de Cálculo de Probabilidades. Ed. Ariel.
Martín Pliego, F.J., Montero Lorenzo, J.M. e Ruiz-Maya L. (1998): Problemas de probabilidad. Ed. AC.
Martín Pliego, F.J., Montero Lorenzo, J.M. e Ruiz-Maya L. (2000): Problemas de inferencia estadística. Ed. AC.
BASIC AND GENERAL
CB1 - That the students have demonstrated to possess and understand knowledge in a study area that starts from the 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 forefront of their field of study
CB2 - That students know how to apply their knowledge to their work or vocation in a professional way and possess the competences that are usually demonstrated through the elaboration and defense of arguments and the resolution of problems within their area of study
CB3 - That students have the ability to collect and interpret relevant data (usually within their area of study) to make judgments that include reflection on relevant social, scientific or ethical issues
CB4 - That students can transmit information, ideas, problems and solutions to both a specialized and non-specialized audience
CB5 - That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy
CG2 - Know how to develop and defend arguments on economic issues at a general level, as well as solve problems on these issues, making use of their knowledge of business reality, theories, models and scientific methods themselves
CG3 - Know how to identify, gather and interpret relevant data on issues related to the business environment, incorporating in the preparation of judgments and proposals the pertinent considerations on its social, scientific or ethical dimension.
TRANSVERSAL
CT1 - -Analysis and synthesis
CT4 - -Information management.
CT5 - -Knowledge of information technology related to the field of study.
CT6 - -Troubleshooting.
CT7 - -Make decisions.
CT8 - -Critical reasoning
CT9 - -Autonomy in learning
CT13 - -Ethical sense
CT16 - -Sensitivity to social and environmental problems
CT22 - -Quality development
SPECIFIC
C2 - Basic elements of descriptive statistics, probability and statistical inference
D6 - Identify the sources of relevant economic information and its content
D8 - Derive from the data relevant information impossible to recognize by non-professionals
D10 - Apply to the analysis of problems professional criteria based on the handling of technical instruments
The course is developed combining expository and interactive teaching, both complemented by individual tutoring and / or in small groups.
The subject will have a virtual classroom on the USC platform where classroom presentations and supporting materials for the course and preparation of the subject will be included.
EXPOSITORY CLASSES
The sessions dedicated to the expository classes are intended to introduce and explain the basic aspects of each topic of the program, providing the necessary additional information that allows the proper development of the autonomous learning process.
INTERACTIVE CLASSES AND PRACTICES WITH COMPUTER
In the interactive classes it is intended that the students learn to apply statistical techniques to the analysis of economic and business reality, differentiating what type of technique to use in each case, how to apply it and what conclusions are obtained from the analysis carried out. Practical problems and activities will be proposed that the students must solve individually and / or in small groups. These interactive practices will be complemented with the realization of computer practices, to acquire skills of handling spreadsheets or other statistical packages useful for data analysis.
SCHEDULED TASKS AND TESTS
Taking computer practices as a reference, continuous evaluation activities may consist of the statistical analysis of empirical phenomena, with real databases, to be carried out throughout the semester, using computer tools. These tasks are intended for the student to acquire skills to carry out statistical analysis of empirical reality, learning to select and apply the appropriate statistical techniques to each phenomenon, to use computer tools for analysis, to correctly interpret the results obtained, and to present / defend the work done using the lexicon of the discipline. Tests can also be carried out to assess the contents developed and their understanding of an individual or group nature.
INDIVIDUAL OR SMALL GROUP TUTORING
Tutoring try that the student has continuous advice from teachers for the development of the proposed activities, many of them to be carried out autonomously by the student body, as well as to answer any questions related to the subject.
Scenario 1: expository and interactive teaching will be totally face-to-face. In the interactive classes the students will work in groups. The tutoring will be primarily face-to-face but it can also be done electronically using email, the virtual classroom or the virtual platform of the USC (Teams).
Scenario 2: face-to-face and virtual teaching will be combined in expository and interactive teaching according to the guidelines established by the Dean's Office or the Rector’s Office for this setting and the sanitary measures that are established at that time. For virtual teaching, the virtual classroom of the subject, the USC platform (Teams) or free platforms that can facilitate electronic mobile learning or M-learning will be used synchronously and / or asynchronously as established by the Center and /. In general, expository teaching may have an asynchronous character and an attempt will be made to make interactive teaching synchronous in order to facilitate the discussion and resolution of practical cases, either face-to-face or telematic according to the guidelines established in this scenario. The tutorship will be primarily by telematic means via email, the virtual classroom of the USC and the virtual platform of the USC (Teams).
Scenario 3: Teaching will be totally virtual. For this teaching, the virtual classroom of the subject and the USC platform (Teams) will be used synchronously and / or asynchronously according to the possibilities established by the Center or the Rector's Office. In general, expository teaching may have an asynchronous character and an attempt will be made to make interactive teaching synchronous in order to facilitate the discussion and resolution of practical cases using the virtual classroom, the USC platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning. The tutorials will be electronically via email, the USC virtual classroom and / or the USC virtual platform (Teams).
At the beginning of the semester, the student may choose between a continuous assessment system and a single assessment system. The recommended evaluation system will be continuous evaluation, using instruments that make it possible to measure the continuous learning of the statistical concepts and methodologies that are the subject of this subject, as well as their application to empirical reality. It will be based primarily on tasks in which the student demonstrates the level of knowledge acquired. The student who attends any test or performs any task will automatically be included in the continuous assessment system. The teaching staff of the subject recommends following this system.
1st OPPORTUNITY
A) Continuous Evaluation System. Assessment instruments and their weight in the final grade:
- Exams: maximum 70% of the total grade (7 points).
- Continuous assessment activities: maximum 30% of the total grade (3 points).
B) Single Assessment System. Students who choose this system will be exclusively graded through the final exam of the subject, which will score over 10 points.
2nd OPPORTUNITY
In the evaluation of the 2nd Opportunity, the students who have chosen the continuous evaluation system will be able to stay in it or switch to a single evaluation system. At the time of the exam, the student will decide whether to remain in the continuous evaluation system (the exam will score 7 points) or to opt for the single evaluation system (the exam will score 10 points). In order to obtain the final grade for the subject, in the first case the continuous assessment score obtained throughout the course will be maintained and added to that of the exam. In the second case, the final grade of the subject will coincide with that obtained in the exam. The students will not have the possibility of recovering the tasks, activities and previous tests pending of completion by the students linked to the continuous evaluation.
To take the exams, it will be necessary to present an official identification document (DNI, Passport ...)
Attendance at activities will be governed by the regulations of the USC. The evaluation in cases of class attendance waiver will be done with the final test valued on the maximum possible grade.
According to the regulations of Permanencia at the USC for Bachelor and Master studies (art. 5.2), the attendance and / or participation in any of the activities subject to evaluation will mean that the final grade of the student is different from “Non Presentado”.
In cases of fraudulent performance of exercises or tests, the provisions of the “Normativa de avaliación do rendemento académico dos estudantes e de revisión de cualificacións” will apply.
Scenario 1: The final individual test will be done in person on the dates established by the Center. The continuous evaluation of the students will be based on the work and / or test carried out or commissioned during the course, in groups or individual, and their active participation in academic activities. It distribution will be: tasks commissioned and delivered (15%), active participation (5%), test (10%). The tasks and evaluable activities throughout the course will be proposed in the face-to-face sessions and in the virtual classroom.
Scenario 2: The final test will be face-to-face if it is possible for the sanitary measures established in this scenario or of a synchronous or asynchronous telematic nature using the virtual classroom of the subject according to the calendar established by the Center. The continuous evaluation will be carried out combining the telematic and face-to-face tasks that are feasible in this scenario. For the group and / or individual telematic tasks and tests of the continuous assessment, the virtual classroom of the subject, the virtual platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning will be used. It distribution will be: tasks and activities commissioned and delivered (20%) and tests (10%). The different evaluable activities throughout the course will be proposed in the face-to-face or telematic sessions developed in this setting and in the virtual classroom.
Scenario 3: The final test will be of a synchronous or asynchronous telematic nature according to the calendar established by the Center. The continuous assessment will be carried out by combining the group and / or individual telematic tasks and tests using the virtual classroom of the subject, the virtual platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning. It distribution will be: tasks and activities commissioned and delivered (20%) and tests (10%). The different evaluable activities throughout the course will be proposed in the telematic sessions developed in this setting and in the virtual classroom.
60 hours of work in the academic activities and 90 hours of autonomous work by the student.
-Having passed Business Statistics I and Business Mathematics I and II.
-Work on the subject daily to take advantage of the classes, to follow the explanations of the subject and to ask any questions in class (very good for the whole group) or in the tutoring.
-Do not stop doing every task that is proposed for its realization.
-Do not leave the subject aside even if the partial evaluations are not positive, as long as you are willing to continue working.
The Scenarios included in the programming are those indicated in the USC Consello de Goberno Agreement of 19/06/2020 "Bases para o desenvolvemento dunha docencia presencial segura. Curso 2020-21” and in the “Directrices para o desenvolvemento dunha docencia presencial segura. Curso 2020-21” of the Comisión for Teaching Planning of 25/06/2020. Under this regulation, the next Contingency Plan was prepared for the adaptation of the sections corresponding to the teaching methodology and the evaluation system for scenarios 2 and 3 so that they are taken into account in the monitoring and accreditation processes of the degree:
a) Teaching methodology
Scenario 2: face-to-face and virtual teaching will be combined in expository and interactive teaching according to the guidelines established by the Dean's Office or the Rector’s Office for this setting and the sanitary measures that are established at that time. For virtual teaching, the virtual classroom of the subject, the USC platform (Teams) or free platforms that can facilitate electronic mobile learning or M-learning will be used synchronously and / or asynchronously as established by the Center and /. In general, expository teaching may have an asynchronous character and an attempt will be made to make interactive teaching synchronous in order to facilitate the discussion and resolution of practical cases, either face-to-face or telematic according to the guidelines established in this scenario. The tutorship will be primarily by telematic means via email, the virtual classroom of the USC and the virtual platform of the USC (Teams).
Scenario 3: Teaching will be totally virtual. For this teaching, the virtual classroom of the subject and the USC platform (Teams) will be used synchronously and / or asynchronously according to the possibilities established by the Center or the Rector's Office. In general, expository teaching may have an asynchronous character and an attempt will be made to make interactive teaching synchronous in order to facilitate the discussion and resolution of practical cases using the virtual classroom, the USC platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning. The tutorials will be electronically via email, the USC virtual classroom and / or the USC virtual platform (Teams).
b) Learning assessment system
Scenario 2: TThe final test will be face-to-face if it is possible for the sanitary measures established in this scenario or of a synchronous or asynchronous telematic nature using the virtual classroom of the subject according to the calendar established by the Center. The continuous evaluation will be carried out combining the telematic and face-to-face tasks that are feasible in this scenario. For the group and / or individual telematic tasks and tests of the continuous assessment, the virtual classroom of the subject, the virtual platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning will be used. It distribution will be: tasks and activities commissioned and delivered (20%) and tests (10%). The different evaluable activities throughout the course will be proposed in the face-to-face or telematic sessions developed in this setting and in the virtual classroom.
Scenario 3: The final test will be of a synchronous or asynchronous telematic nature according to the calendar established by the Center. The continuous assessment will be carried out by combining the group and / or individual telematic tasks and tests using the virtual classroom of the subject, the virtual platform (Teams) and / or free platforms that can facilitate electronic mobile learning or M-learning. It distribution will be: tasks and activities commissioned and delivered (20%) and tests (10%). The different evaluable activities throughout the course will be proposed in the telematic sessions developed in this setting and in the virtual classroom.
Carlos Pio Del Oro Saez
- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- carlospio.deloro [at] usc.es
- Category
- Professor: University Lecturer
Marina Lois Mosquera
Coordinador/a- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- Phone
- 881811521
- marina.lois [at] usc.es
- Category
- Professor: University School Lecturer
| Tuesday | |||
|---|---|---|---|
| 09:15-11:15 | Grupo /CLE_01 | Galician | Classroom 07 |
| 11:45-13:45 | Grupo /CLE_02 | Galician | Classroom 20 |
| 15:30-17:30 | Grupo /CLE_03 | Spanish | Classroom 07 |
| Wednesday | |||
| 09:15-10:45 | Grupo /CLE_02 | Galician | Classroom 08 |
| 17:15-18:45 | Grupo /CLE_03 | Spanish | Classroom 07 |
| Friday | |||
| 11:15-12:45 | Grupo /CLE_01 | Galician | Classroom 07 |
| 01.20.2022 09:00-12:00 | Grupo /CLE_02 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_06 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_04 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_01 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_02 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLE_01 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_07 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_05 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_03 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLE_03 | Classroom A |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_02 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_07 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_05 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_03 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLE_03 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLE_02 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_06 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_04 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLE_01 | Classroom B |
| 01.20.2022 09:00-12:00 | Grupo /CLIL_01 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_03 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLE_01 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLE_03 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLE_02 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_06 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_04 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_01 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_02 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_07 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_05 | Classroom A |
| 06.20.2022 15:00-18:00 | Grupo /CLE_02 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_04 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_06 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_01 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_02 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLE_01 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_07 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_05 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLIL_03 | Classroom B |
| 06.20.2022 15:00-18:00 | Grupo /CLE_03 | Classroom B |