Business Statistics I

To provide the students with the knowledge and use of the statistical techniques that are necessary for the descriptive and probabilistic analysis of economic and business data, together with the methodology of the main statistics that are available for us.
The contents presented in the classroom will be applied in the computers, according to the possibilities of the Faculty’s Computer Room.

UNIT 1. INTRODUCTION.
1.1. The science of Statistics. Definition and content.
1.2. General concepts of Statistics.
1.3. Sources of statistic data: types, classification and sampling.

UNIT 2. DESCRIPTIVE ANALYSIS OF A VARIABLE.
2.1. Distributions of frequencies.
2.2. Graphical representations.
2.3. Measures that characterize the distribution of a variable.
2.3.1. Position measures.
2.3.2. Dispersion measures.
2.3.3. Form measures.
2.4. Moments in one-dimensional distributions.
2.5. Concentration measures.

UNIT 3. DESCRIPTIVE ANALYSIS OF TWO VARIABLES.
3.1. Two-dimensional distributions. Tabulation and graphical representations.
3.2. Marginal and conditioned distributions.
3.3. Statistical dependence and independence.
3.4. Moments in two-dimensional distributions. Covariance.
3.5. Generalization of n-dimensional characteristics.

UNIT 4. TECHNIQUES OF REGRESSION AND CORRELATION
4.1. Introduction to the theories of regression and correlation.
4.2. Simple linear correlation.
4.3. Association and correlation coefficients.
4.4. Regression of the mean and least-square regression.
4.5. Simple linear regression.
4.5.1. Goodness of fit in a regression.
4.5.2. Applications. Prediction.
4.6. Non-linear fit and other models of regression.
4.7. Elasticity.

UNIT 5. INDEX NUMBERS
5.1. Rates of variation. Definition and classification of index numbers.
5.2. Problems for elaborating complex indexes. Change of base.
5.3. Indexes of prices, quantities and value.
5.4. Properties of index numbers.
5.5. Deflation of economic series.
5.6. Participation and repercussion.

UNIT 6. SOCIO-ECONOMIC STATISTICS

7.1. Consumer Prices Index.
7.2. Industrial Prices Index.
7.3. Industrial Production Index.
7.4. Labour Force Survey.
7.5. Household Budget Survey.
7.6. Other economic indicators.

UNIT 7. TEMPORAL SERIES.
6.1. Introduction to the classical analysis of temporal series. Outlines.
6.2. Analysis of components. Deseasonalization.

Basic:

TOMEO, V. ; UÑA, ISAÍAS (2009) Estadística descriptiva. Garceta, Madrid

MARTÍN PLIEGO, F.J. (2004). Introducción a la Estadística Económica y Empresarial: Teoría y práctica. Thompson Paraninfo S. A., Madrid.

ESTEBAN GARCÍA, J. y otros (2005). Estadística descriptiva y nociones de probabilidad. Thomson, Madrid.

Theory and practice.

CASAS, J., CALLEALTA, J., NÚÑEZ, J., TOLEDO, M. e UREÑA, C. (1986). Curso básico de Estadística Descriptiva. INAP, Madrid.

CASAS SÁNCHEZ, J. M., SANTOS PEÑA, J. (1995). Introducción a la Estadística para Economía y Administración de Empresas, vol 1. Centro de Estudios Ramón Areces, S.A., Madrid.

DURÁ, J.M., LÓPEZ, J.M. (1988). Fundamentos de Estadística. Ed. Ariel Economía, Barcelona.

ESCUDER VALLÉS, R. (1997). Métodos estadísticos aplicados a la Economía. Ariel, Barcelona.

FERNÁNDEZ CUESTA, C., FUENTES GARCÍA, F. (1995). Curso de Estadística Descriptiva. Ariel Economía, Barcelona.

FERNÁNDEZ, C., FUENTES, F. (1995). Curso de Estadística Descriptiva: Teoría y Práctica. Ed. Ariel Economía, Barcelona.

GARCÍA BARBANCHO, A. (1991). Estadística elemental moderna. Ariel Economía, Barcelona.

KAZMIER, L., DIAZ, A. (1993). Estadística aplicada a la Administración y a la Economía. Ed. McGraw-Hill Interamericana de México, México

LLORENTE GALERA, F., MARTÍN FERIA, S. Y TORRA PORRAS, S. (2000). Principios de estadística descriptiva aplicada a la empresa. Centro de Estudios Ramón Areces, D.L. Madrid.

MARTÍN-GUZMÁN, P., MARTÍN PLIEGO, F.J. (1987). Curso básico de Estadística Económica. AC, Madrid.

MARTÍN PLIEGO, F.J. (1994). Introducción a la Estadística Económica y Empresarial. AC, Madrid.

MONTIEL, A.M., RIUS, F., BARÓN, F.J. (1997). Elementos básicos de Estadística Económica y Empresarial. Prentice-Hall, Madrid.

PÉREZ SUÁREZ, R. e outros (1993). Análisis de datos económicos 1. Métodos Descriptivos. Pirámide, Madrid.

RIOBÓO, J.M., TATO, M. (1992). Estadística Económica y Empresarial I: evolución histórica, concepto y método de la estadística económica y empresarial. GIC Ediciones, Santiago.

RIOBÓO, J.M.; DEL ORO, C.P. (2000). Representaciones gráficas de datos estadísticos. AC, Madrid.

URIEL, E., MUÑÍZ, M. (1988). Estadística Económica y Empresarial. Teoría y ejercicios. AC, Madrid.

VISAUTA VINACUA, B., BATALLE DESCALS, P. (1986). Métodos estadísticos aplicados. Tomo 1: Estadística descriptiva. Promociones y Publicaciones Universitarias, S.A. (PPU), Barcelona.

Exercises and problems.

ARENALES, C. (1978) Libro de ejercicios de estadística económica. CECA, Madrid.

BARÓ LLINÁS, J. (1985). Estadística descriptiva. Aplicaciones económico-empresariales. Parramón, Barcelona.

CANDEL ATO, J., MARÍN PÉREZ, A. e RUIZ GÓMEZ, J.Mª. (1991). Problemas de estadística aplicada 1: estadística descriptiva. Promociones y Publicaciones Universitarias (PPU), Barcelona.

GARCÍA BARBANCHO, A. (1973). Ejercicios de Estadística Descriptiva para economistas. Ariel, Barcelona

MARTÍN PLIEGO, F. J. (1987). Curso práctico de estadística económica. AC, Madrid.

PERALTA ASTUDILLO, M.J. et al. (2000). Estadística: problemas resueltos. Ed. Pirámide. Madrid

SANZ, J. A., BEDATE, A., RIVAS, A., GONZÁLEZ, J. (1996). Problemas de estadística descriptiva empresarial. Ariel, Barcelona.

SPIEGEL, R.S. (1991) Estadística. Ed. Mc Graw-Hill Interamericana de España, Madrid

Computing.

GONZÁLEZ-CONDE LLOPIS, C. (2000). Estadística aplicada con Excel 97. Ediciones de la Universidad Autónoma de Madrid, D.L. Madrid.

Presentation of data in the media and use of the statistical language.
Calculation and summary of the numerical and qualitative information.
Statistical analysis of the existing information.
Get relevant information data unrecognizable by non-professionals.
Apply professional criteria to analyze problems based on the management of statistical tools.
Use of computer software for obtaining statistical results.
Obtaining of detailed statistical information

Big group blackboard sessions: It will be used for activities that do not require an active participation of the students, and the number of students by group is not a critical factor for his development: exposition, presentation of audiovisual materials, conferences,..

Reduced group sessions: Activities that require an active participation of the students: seminars, discussion of practical cases, resolution of problems, work with texts or data, computer practical,...

Tutorial reduced groups: Orrientation activities and tutorial for the student, preparation of the exhibitions, research and selection of bibliographic material and statistical sources, review of practices or problems...

Will use the virtual classroom.

Language:

Group Language/s
1 Spanish
2 Spanish / Galician
3 Galician
4 Spanish

The evaluation of the course will be as follows:

- 70% of the final grade is based on the written exam.
- 30% of the final grade is of continuous evaluation, based on activities done in class (tests, exercises solved in class, …), which require assistance on a regular basis in order to be able to take part in all of them.

For students that do not participate in any of the continuous evaluation activities, the final exam will be worth 100% of the grade.

In order to pass the course a minimum grade of 5 out of 10 is required in any of the two cases.

The conditions of the second phase of evaluation (the extraordinary exam of July) will be the same as in January, unless the student decides during the exam to give up the continuous assessment grade. In this case the grade of the retake exam will count for 100% of the final grade.

In order to take any exam. An official document will be required: Identity card (DNI), University Student Card, passport, etc…
-
The test of continuous evaluation will take place during the classes and may be announced in them.

Other details about these basic criteria may be specified in class.

Activity:
Individual autonomous or in group study: 60 hours
Writing of exercises, conclusions or other works: 5 hours
Readings, recommendations, activities in libraries or similar: 15 hours
Preparation of oral presentations or similar: 10
Total hours: 90 hours

The mathematical language is necessary for the development of the subject since that is the language in which Statistics is expressed. So, students must do an effort at the beginning of the year for adapting to a language that is not common for them. That difficulty will be soon overcome because the contents are presented in a gradual way.
Students need to acquire the necessary tools for interpreting those results that have been obtained or collected from differents sources. Discussions in the classroom are a useful tool for understanding the presented contents.

The possible complementary information to follow the course will be facilitated in classroom.