Universidad Pública de Navarra - Nafarroako Univertsitate Publikoa

Module/Subject matter

Statistics.

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Contents

An introduction to basic statistical concepts on data analysis, such as Descriptive Analysis of Univariate and Bivariate data real data, Description and Analysis of Temporal Data and Index numbers. Basic probability notions and an introduction to random variables.

Excel will be the usual framework for data analysis. Moreover students will be briefly introduced to the statistical package R Commander.

MiAulario will provide a communication channel between students and instructors.

• Chapter 1: Introduction to Statistics for Economy and Business: Statistical applications in Business, types of data, data sources.
• Chapter 2: Descriptive analysis of univariate data: frequency tables, graphical representations of data and  statistical measures.
• Chapter 3 : Descriptive analysis of bivariate data: contingency tables and regression analysis.
• Chapter 4: Index numbers: simple and composite indexes, applications and variation rates.
• Chapter 5: Time series analysis: Numeric and graphical description of temporal data, time series components.
• Chapter 6: Probability and  introduction to discrete random variables.

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Descriptors

An introduction to basic statistical concepts on data analysis, stressing on the role of Statistics in Economy and Business.

Topics of interest will cover sources of statistical data, data files management; descriptive analysis of univariate and bivariate data real data; description and analysis of temporal data and Index numbers.  The use of different statistical packages will be fundamental in data analysis. Basic notions of probability and random variables are also introduced.

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General proficiencies

• GP01:  A capacity for analysis and synthesis.
• GP02:  A capacity for organisation and planning.
• GP03:  Oral and written communication in their mother tongue.
• GP05: Computer skills relevant to the field of study.
• GP06: The ability to search for and analyse information from different sources.
• GP07: The capacity to solve problems.
• GP09: The capacity to work as part of a team.
• GP14: Critical and self-critical skills.
• GP17: A capacity for self-reliant learning.

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Specific proficiencies

• SP02: To identify sources of economic information relevant to their particular enterprise and their contents.
• SP03: To discern information and data relevant to their particular enterprise which a non-professional would be unable to recognise.
• SP04: To analyse business management problems, applying professional criteria based on the use of technical instruments.
• SP09: To form part of any functional area within an enterprise or organization and perform any managerial task required within it confidently.

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Learning outcomes

At the end of the semester students must be able to: 

LO1 – Understand the notions of Univariate and Bivariate Descriptive Statistics and apply them according to  the different types of variables to be analyzed.    
LO2 – Analyze the temporal evolution of socio-economic data by computing index numbers and time series analysis.
LO3 – Use software for data handling. 
LO4 – Prepare and submit reports on statistical analysis of economic data obtained consulting appropriate information sources and computer processing.
LO5 – Understand the notion of probability, know its properties and apply them to solve problems arising from socio-economic environments. 

The accompanying table relates the above learning outcomes to those contents, formative and evaluation activities detailed in the following sections:  

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Methodology

From a total of 60 hours, 40 will be devoted to theoretical, problem and computer sessions.

The remaining period will be devoted to check  students’ individual progress and to evaluate their work. These sessions will be scheduled along the semester.

Being the aim of this course mainly practical, theoretical and computer sessions will be alternated:

a) Theoretical sessions will consist on the exposition of the contents by the instructor. Students will be encouraged to participate by asking and answering short questions and solving exercises, so they keep their attention in the development of the lecture.

b) Computer sessions will be guided by the instructor. Students will be asked to look for data and make use of the provided software to carry out different statistical analyses by using those notions previously introduced during the lectures.

MiAulario will be used as the course web page.

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Languages

English.

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Evaluation

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Agenda

Chapter 1: Introduction to Statistics for Economy and Business: Statistical applications in Business, types of data, data sources.
- Statistics. Steps of a statistical study and different statistical areas.
- Enter data into an Excel spreadsheet and other statistical packages.
- Types of variables and scales of measurement.

Chapter 2: Descriptive analysis of univariate data: frequency tables, graphical representations of data and statistical measures.
- Frequency tables and graphical representations.
- Measures of central and non-central location.
- Box-plots.
- Measures of absolute and relative variability.
- Standarized scores.
- Measures of shape.

Chapter 3: Descriptive analysis of bivariate data: contingency tables and regression analysis.
- Contingency tables.
- Covariance and correlation.
- Statistical and Functional dependence.
- Simple linear regression: Least squares method.
- Non linear regression models.

Chapter 4: Index numbers: simple and composite indexes, applications and variation rates.
- Introduction. Simple and composite indexes.
- Properties. Change in base period.
- Consumer Price index and other indexes. Gini Index.
- Variation rates.

Chapter 5: Time series analysis. Numeric and graphical description of temporal data, time series components.
- Introduction.
- Graphical analysis of time series.
- Time series components and seasonal models.
- Trend analysis and analysis of seasonality.

Chapter 6: Probability and introduction to discrete random variables.
- Basic terminology of probability.
- Probability Rules.
- Conditional probability and independence.
- Bayes' Theorem.
- Discrete random variables

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Bibliography

Access the bibliography that your professor has requested from the Library.

Basic:

- PANIELLO, I.; RIVERA, R.; PORTILLA, M. (2011) "Statistical tools for socioeconomic data analysis". EDS.
- PANIELLO, I.; GARCIA, M.; RIVERA, R.; PORTILLA, M. (2012) "Basic Statistics with Microsoft Excel and R-Commander". EDS.
- NEWBOLD, P., CARLSON, W.L.; THORME, B. (2008) "Statistics for Business and Economics", Pearson Ed.

Complementary:

- ARNALDOS, F.; DÍAZ, T.; FAURA, U.; MOLERA, L.; PARRA, I. (2003) "Estadística Descriptiva para Economía y Administración de Empresas. Cuestiones tipo test y ejercicios con Microsoft Excel". 2ª edición revisada. Editorial AC-Thomson.
- CARRASCAL ARRANZA, U. (2007) "Estadística descriptiva con Microsoft Excel 2007". Editorial Rama.
- LIND; MARCHAL; WATHEN (2008) "Estadística aplicada a los negocios y la economía". 3ª edición en español (13ª en inglés). Ed. McGraw-Hill Interamericana.
- MARTÍN-PLIEGO, F.J. (2004) "Introducción a la estadística económica y empresarial: teoría y práctica". 3ª edición revisada. Editorial Thomson.

Students will be encouraged to use MiAulario. There students will find material for both theoretical lessons and computing lab sessions, together with data files and any other recommended additional material.

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Location

Campus  Arrosadía. Building Mi Aulario.

Practice sessions in computer rooms.

Lectures in rooms as published at the Faculty website (follow link):
http://www.unavarra.es/fac-economicas/studies/degree/international-double-degree-in-economics-and-business-ddministration-and-management+/overview?submenu=yes&languageId=1

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