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Introducción a la Estadística Económica
- Clases Expositivas (28 Hours)
- Prácticas de Laboratorio (6 Hours)
- Prácticas de Aula/Semina (21 Hours)
The course Introduction to Economic Statistics is a basic training in a Business Administration degree. It is a course common to the degrees in Economics, Accounting and Finance and Labour Relations and Human Resources, which are also part of the course catalog of the School of Economics and Business. For the degrees in a Business Administration, Economics and Accounting and Finance this subject is in the module Quantitative Methods and in the Statistical matter; whereas for the degree in Labor Relations and Human Resources it is in the matter Sociology of the Work and Technologies of Social Investigation.
From an educational perspective, two reasons can be highlighted in order to justify the teaching of statistics at undergraduate level:
1. Statistics is useful for a future career in economics-business.
2. Knowledge of statistics as a part of general education is desirable for all citizens.
Indeed, professionals in economics and business regularly deal with large amounts of numerical data that require adequate treatment to be really informative and useful in decision-making. Also, mass-media give us daily news based on statistical information on different areas of present social and economic conditions (unemployment numbers, TV ratings, opinion polls, etc.) to be interpreted properly by the public.
In this context, the course in statistics in the first undergraduate year aims to introduce students to statistical reasoning, providing basic training to enable them to apply different analytical tools to economic and social problems. This training will be supplemented with compulsory and optional courses in later years.
The course has no prerequisites. It is recommended that the student should be competent in mathematics, in any of its options, at secondary (high school) level.
To achieve the overall objectives, the course will pay attention to the following general skills:
Degree in Business Administration:
- Capacity for analysis and synthesis.
- Learning capacity.
- Ability to search and analyze sources of information in the field of work.
- Ability to use computer tools and communication technologies.
- Ability to work autonomously.
- Critical and self-critical capacity.
- Capacity to make decisions.
- Ability to apply knowledge in practice.
- Concern for quality and a job well done.
- Have ethical values and behaviors.
- Integrate the principles of equal treatment and opportunities between women and men in the workplace
Degree in Accounting and Finance:
- Capacity for analysis and synthesis.
- Ability to use computer tools related to the field of study.
- Ability to search, analyze and interpret information from various sources.
- Capacity to solve problems.
- Capacity to make decisions.
- Critical and self-critical capacity.
- Ethical commitment at work and motivation for quality.
- Autonomous learning capacity.
- Ability to apply knowledge to practice.
Degree in economics:
- Capacity for analysis and synthesis.
- Learning capacity.
- Ability to search and analyze sources of information in the field of work.
- Ability to use computer tools and communication technologies.
- Ability to work autonomously.
- Critical and self-critical capacity.
- Capacity to make decisions.
- Ability to apply knowledge in practice.
- Concern for quality and a job well done.
Degree in Labor Relations and Human Resources:
- Ability to manage information.
- Ability to solve problems.
- Decision making.
- Capacity for analysis and synthesis.
- Autonomous Learning.
- Capacity for critical and self-critical reasoning.
The specific skills that are developed in the subject are the following:
Degrees in Business Administration and Economics:
- To identify and apply the appropriate quantitative tools for the analysis of economic information.
- To manage and interpret specific software for data processing.
- To transmit information, ideas, problems and solutions from the economic field and business management to both a specialized and non-specialized audience.
Degree in Accounting and Finance:
- To apply quantitative techniques in the analysis of financial information.
Degree in Labor Relations and Human Resources:
- Ability to transmit and communicate in writing and orally using the terminology of labor relations and human resources.
- Ability to interpret data and socioeconomic indicators related to the labor market.
- Ability to apply quantitative social research techniques to the workplace.
- To Apply knowledge of labor relations and human resources to practice.
The previous general and specific competences are specified in the following learning outcomes:
Degree in Business Administration and Economics:
- To apply descriptive statistics tools to solve problems in the economic and business field.
- To describe the basic concepts linked to the preparation of socioeconomic statistics.
- To manage statistical software for problem solving.
Degree in Accounting and Finance:
- To apply descriptive statistics tools to solve problems in the economic and business field.
- To describe the basic concepts linked to the preparation of socioeconomic statistics.
Degree in Labor Relations and Human Resources:
- To apply descriptive statistics tools to solve problems in the economic and business field.
- To calculate indices and rates for the analysis of the temporal variation of economic magnitudes.
- To manage statistical software for problem solving.
The program is divided into 10 lessons grouped into three blocks: a first block, corresponding to lessons 1-4, focuses on the study of univariate statistics. The second block, which covers lessons 5-6, studies sets of variables and their relationships. The common feature of the third block, corresponding to lessons 7-10, is the analysis of variables from a temporal approach.
5.1. Program in brief
Lesson 1: Organization and presentation of data: statistical sources
Lesson 2: Measures of central tendency and partition values
Lesson 3: Measures of dispersion
Lesson 4: Measures of inequality and poverty
Lesson 5: Measures of correlation and association
Lesson 6: Simple regression
Lesson 7: Index Numbers: rates and properties
Lesson 8: Index numbers: standard formulas, change and contributions
Lesson 9: The Consumer Price Index (CPI) and its applications
Lesson 10: Time series
5.2. Detailed program and learning objectives
Lesson 1. Organization and presentation of data: statistical sources
1.1 .- Sources of information: censuses and samples 1.2 .- Types of statistical information 1.3 .- Presentation of data: tables and graphs 1.4 .- National and European statistical systems 1.5 .- Statistical sources of economic information |
Objectives:
The lesson has two distinct parts, the first one dealing with the introduction of basic statistical concepts and terminology and also with the methods of tabulation and graphical representation of statistical information. The second part is devoted to the study of the general features of the official statistical system and some socio-economic statistical sources.
From this perspective, specific learning objectives to be pursued by students are to:
- Describe data collection procedures and to distinguish between census and sample surveys.
- Manage frequency tables of grouped and ungrouped data, differentiating the types of frequencies and their relationships.
- Choose appropriate graphs to represent a set of data and recognize errors in graphical representations present in the media.
- Know the basic characteristics of national and European statistical systems.
- Describe the main characteristics of some socio-economic statistics compiled by the INE.
- Search for socio-economic statistical information on the websites of official statistical agencies.
Additional Material:
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapters 1 and 2]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 1.
INE web: http://www.ine.es
Lesson 2. Measures of central tendency and quantiles
2.1. Measures of central tendency: averages 2.2. Quantiles |
Objectives:
This lesson introduces the different types of measures for summarizing or synthesizing the behaviour of a data set. The approach followed in this lesson will help students to achieve the following learning objectives:
- Calculating and interpreting various averages: arithmetic mean, weighted mean, median and mode.
- Comparing the properties of the arithmetic mean, median and mode.
- Calculating and interpreting various quantiles (deciles, quartiles, and percentiles).
Additional Material:
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapter 3]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 2.
Lesson 3. Measures of dispersion
3.1 .- Measures of absolute dispersion 3.2 .- Measures of relative dispersion 3.3 .- Standardized variables |
Objectives:
This lesson presents the different types of measures for analyzing the variability of a dataset and the representativeness of the averages. It also studies the concept of the standardized variable. The learning objectives to be achieved are:
- To quantify the variability or dispersion of a distribution through measures of absolute dispersion.
- To study the properties of the variance and standard deviation.
- To calculate and interpret coefficients of variation.
- To compare the representativeness of averages.
- To compare values from different distributions by means of standardized variables.
Additional Material:
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapter 3]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 3.
Lesson 4. Measures of inequality and poverty
4.1 .- Poverty measures 4.2 .- Economic inequality 4.3 .- The Lorenz curve and the Gini index |
Objectives:
This lesson introduces the need to quantify the disparities in the distribution of economic variables, such as family income, wages, etc., by a set of inequality and poverty indicators. The learning objectives to be achieved are to:
- Appreciate the importance of the phenomenon of economic inequality.
- Plot Lorenz curves and interpret their meaning in relation to inequality.
- Quantify the inequality by the Gini index.
- Apply the desirable properties of inequality measures.
- Define poverty.
- Calculate and interpret measures of poverty.
Additional Material:
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 4.
Lesson 5. Measures of correlation and association
5.1. Two-dimensional distributions 5.2. Marginal distributions 5.3. Statistical dependence and independence 5.4. Measuring correlation Measures of association in contingency tables 5.5. Measuring correlation |
Objectives:
This lesson addresses the joint study of two characters and the possible relationships between them. The learning objectives to be achieved are to:
- Appreciate the interest of the joint study of several characters.
- Construct and interpret tables and two-dimensional scatter plots.
- Build marginal distributions.
- Recognize and interpret the possible relationship between two variables: functional independence, statistical independence and statistical dependence.
- Quantify the degree of association between two attributes by Pearson’s contingency coefficient.
- Calculate and interpret measures of linear dependence: covariance and linear correlation coefficient.
Additional Material
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapter 3]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 5.
Lesson 6. Simple Regression
6.1 .- Correlation and regression 6.2 .- Least squares regression 6.3 .- Goodness of fit analysis 6.4 .- Forecasting with causal models |
Objectives:
This lesson examines the procedures for building explanatory models from the joint information of two statistical variables mutually correlated. From this perspective, specific learning objectives to be pursued by students are to:
- Distinguish the concepts of correlation and regression and analyze the connection between them.
- Calculate regression lines by least squares adjustment.
- Interpret the coefficients of the regression line.
- Analyze the goodness of fit of a model by the coefficient of determination.
- Calculate predictions from causal models and to analyze its reliability.
Additional Material:
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapter 13]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 6.
Lesson 7. Index numbers: rates and properties
7.1 .- Simple index numbers and rates 7.2 .- Synthetic index numbers 7.3 .- Properties of the index numbers |
Objectives:
The last part of the program is devoted to the study of the temporal evolution of economic variables. Specifically, this lesson addresses the comparison of the values of a variable between different time periods through the calculation of index numbers and rates of change. The learning objectives to be achieved are to:
- Obtain and interpret simple temporal and spatial indices.
- Calculate and interpret different types of rates of change (monthly, annual...)
- Describe the desirable properties of index numbers.
Additional Material:
BERENSON, M.L., et al. (2010): Basic Business Statistics. Concepts and applications. Pearson International. [Chapter 16]
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 8.
Lesson 8. Index numbers: standard formulas, change and contributions
8.1.- Standard formulas for price and quantity index numbers 8.2.- Chain indices 8.3.- Change of an index number and individual contributions |
Objectives:
This lesson explores the formulas most commonly used for constructing a synthetic index in the field of economics. It also addresses the measurement of the change on a synthetic index between two points in time. The learning objectives to be achieved are:
- Obtaining and interpreting price and quantity Laspeyres’ and Paasche’s formulae.
- Calculating rates and analyzing advantages and disadvantages of chain index numbers.
- Calculating and interpreting the relative change of a weighted-average composite index and the individual effect of each component.
Additional Material:
Notes on the lesson available at the Virtual Campus www.campusvirtual.uniovi.es
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 9.
Lesson 9. The Consumer Price Index (CPI) and its applications
|
Objectives:
This lesson continues with the study of index numbers and extends its applications in an economic context. The lesson focuses on the Consumer Price Index (CPI) and its role as a deflator. These contents will allow the students to achieve the following objectives:
- To describe the objectives and the basic features of the Spanish CPI (base 2016)
- To describe the basic features of the HCPI.
- To distinguish between variables at current prices and constant prices.
- To define the concept of deflation and transform series into constant prices in order to analyze the real evolution of economic variables.
Additional Material:
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [online]. Chapter 10.
INE Web http://www.ine.es
- CPI and HCPI methodologies
- Household Budget Survey (HBS) methodology
Lesson 10. Time series
10.1 .- Temporal evolution of variables 10.2 .- Components of a time series 10.3 .- Trend analysis 10.4 .- Analysis of seasonal variations 10.5 .- Seasonal adjustment 10.6 .- Forecasting |
Objectives:
This lesson begins the study of time series from a classical perspective, through the analysis of its components. The approach taken in this lesson must allow the students to achieve the following learning objectives:
- To describe the components of a time series.
- To identify the type of model of a time series.
- To obtain the trend by moving average methods and adjustment.
- Application of the appropriate procedure to identify the seasonal component.
- Interpreting the seasonal component.
- Adjusting seasonally a time series.
- Obtaining forecasting of time series and analyze its reliability.
Additional Material:
BERENSON, M.L.; LEVINE, D.M. y KREHBIEL, T.C. (2010): Basic Business Statistics. Concepts and applications. Pearson International. Tema 16.
PÉREZ, R.; CASO, C.; RÍO, M.J. y LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [en línea]. Temas 11 y 12.
The program is divided into lessons that correspond to weekly teaching units. The face-to-face teaching is based on two types of activities: lectures and classroom practices, with weekly sessions of an hour and a half each. These activities are complemented by practical sessions in the computer lab.
In this context, the work plan for the activities will be:
- Lectures: These classes will consider the overall motivation of the subject. They are based on real situations in the economic field and will give an overview of the theoretical part of each lesson, with particular attention to the key concepts and the most important developments.
- Classroom practices: These sessions will solve theoretical and practical issues and statistical assumptions related to economics and business with the support of the tools introduced in the lectures.
- Lab Sessions: The students will have in these sessions the opportunity to study theoretical problems as well as to solve practical problems in smaller sub-groups, will facilitate tracking of their activities by the professor. Working with the worksheet will be one of the main tools in these sessions.
The teaching methodology and work plan is based on the Virtual Campus www.campusvirtual.uniovi.es in two ways:
- As the reference site to look up and download educational resources, since students have access to all the materials necessary for the monitoring of the course beforehand: lectures presentations, instructions and data bases for practice sessions, a collection of suggested exercises for autonomous work and solved problems in every part of the program.
- As an area of active participation for the student in the process of learning: self-assessment tests, discussion forums, on-line tutorials, etc.
The materials in the Virtual Campus are supplemented by references to handbooks of economic statistics, available for consulting and loaning from the Library of Legal and Social Sciences http://buo.uniovi.es/, and relevant web references with statistical resources.
The following table summarizes the schedule for each type of activity of the course. Besides the classroom activities described above, an additional 60% is also included corresponding to the total workload of activities that do not require attendance. They are distributed among the study of the topics of the course and proposed tasks and evaluable activities.
WORK REQUIRING ATTENDANCE | WORK NOT REQUIRING ATTENDANCE | |||||||
Lessons | Total Hours | Lectures | Practical classes | Computer Classroom Practices | Evaluations Sessions and other activities | Total | Individual Work | Total |
1 | 6.5 | 2 | 1.5 | 3.5 | 3 | 3 | ||
2 | 11.75 | 3 | 2 | 0.75 | 5.75 | 6 | 5.5 | |
3 | 11.25 | 2.5 | 1.5 | 0.75 | 4.75 | 6.5 | 6.5 | |
4 | 11.75 | 3 | 2 | 0.75 | 5.75 | 6 | 6 | |
5 | 12.25 | 3 | 2 | 0.75 | 5.75 | 7 | 7.5 | |
6 | 14 | 3 | 2.5 | 1 | 6.5 | 7.5 | 6.5 | |
7 | 12.5 | 3 | 2 | 1 | 6 | 6.5 | 8 | |
8 | 15.5 | 3.5 | 3 | 1 | 7.5 | 8 | 5.5 | |
9 | 9 | 2 | 1.5 | 3.5 | 5.5 | 5.5 | ||
10 | 13 | 3 | 3 | 6 | 6 | 7 | ||
Final exam | 32 | 5 | 5 | 27 | 27 | |||
Total Hours | 150 | 28 | 21 | 6 | 5 | 60 | 90 | 90 |
(%) | 18.67% | 14.00% | 4.00% | 3.33% | 40.00% | 60.00% | 60.00% |
Below is an indicative timetable, common to all groups of the course. It may vary slightly depending on the specific weekly schedule of each group.
Week | Work requiring attendance | Work not requiring attendance |
1 | Introduction to the course Lesson 1.- Organization and presentation of data. Statistical sources | Study of lesson 1 Look up statistical databases at the INE website |
2 | Lesson 2.- Measures of central tendency and partition values | Study of lesson 2 |
3 | Lesson 2.- Measures of central tendency and partition values Lesson 3.- Measures of dispersion | Study of lesson 2 and 3 |
4 | Lesson 3.- Measures of dispersion Lesson 4: Measures of inequality and poverty | Study of lesson 3 and 4 |
5 | Lesson 4: Measures of inequality and poverty Lesson 5: Measures of correlation and association | Study of lesson 4 and 5 |
6 | Lesson 5: Measures of correlation and association | Study of lesson 5 |
7 | Lesson 6.- Simple Regression | Study of lesson 6 |
8 | Lesson 6.- Simple Regression Lesson 7.- Index numbers: rates and properties | Study of lesson 6 and 7 |
9 | Lesson 7.- Index numbers: rates and properties Lesson 8: Index numbers: standard formulas, change and contributions | Study of lesson 7 and 8 |
10 | Lesson 8: Index numbers: standard formulas, change and contributions | Study of lesson 8 |
11 | Lesson 8: Index numbers: standard formulas, change and contributions | Study of lesson 8 |
12 | Lesson 9: The Consumer Price Index (CPI) and its applications Lesson 10.- Time series | Study of lesson 9 Look up the CPI data in the website of the INE |
13 | Lesson 10.- Time series | Study of lesson 10 |
14 | Lesson 10: Time series | Study of lesson 10 Preparation of the final exam |
The evaluation of the course is based on two elements:
- Continuous assessment, which will value the effort and work developed by the student throughout the course by means of different types of individual activities.
- Final exam, which will assess the knowledge acquired by the student as well as his/her capabilities to apply the statistical tools when analyzing and solving problems in the field of economics and business.
Grading system
The final grade will be calculated in all examination periods as follows:
- If the grade in the final exam is 3 out of 10 or higher, the final grade will be calculated as a weighted mean of the grades in the final exam (60%) and the continuous assessment (40%).
- If the grade in the final exam is lower than 3, then the final course grade will be FAIL and the maximum final score will be 4.5, even if the weighted average was higher.
Continuous assessment activities will be carried out throughout the semester in which the subject is taught within the deadlines established by the teachers. These tests will evaluate the level of knowledge acquired by the student at each moment of time and the fulfillment of the learning objectives throughout the semester. The qualification of these continuous assessment tests will be kept in all the calls of the corresponding academic year.
In an exceptional manner, in the extraordinary call in January, the students included in the proceedings may choose to take an additional test that allows them to obtain 100% of the grade.
It is recalled that the Code of Ethics of the University of Oviedo is in force and is applicable. It is available from the following link: https://www.uniovi.es/conocenos/uniovi/nosotros/etica.
Differentiated Assessment
For students in the differentiated assessment system, the same grading system will be applied, with continuous assessment activities replaced by theoretical and practical questions about the different contents of the program.
The main teaching resources of the subject will be available on the Virtual Campus www.campusvirtual.uniovi.es (presentations, case studies, documents, etc).
The basic bibliography is a freely downloadable online book (in Spanish) and a textbook (in English). These references, as well as other study material for the course, are the following:
Basic Bibliography
BERENSON, M.L., LEVINE, D.M. and T.C. KREHBIEL (2010): Basic Business Statistics. Concepts and applications. Pearson International.
PÉREZ, R.; CASO, C.; RÍO, M.J. and LÓPEZ, A.J. (2011): Introducción a la Estadística Económica. [in Spanish] < freely downloadable at http://goo.gl/Tkn8q >..
Further reading
CASAS, J.M. y J. SANTOS (2002): Introducción a la Estadística para Economía (2ª ed.). Ed. Centro de Estudios Ramón Areces.
MARTÍN, F.J. (2004): Introducción a la Estadística Económica y Empresarial (teoría y práctica) (3ªed.). Ed. Thomson-Paraninfo.
MARTÍN-GUZMÁN, P.; TOLEDO, I.; LÓPEZ, F.J. y N. BELLIDO (2006): Manual de Estadística Descriptiva. Ed. Civitas.
MONTERO, J.Mª. (2000): Estadística para Relaciones Laborales. Ed. AC.
MOORE, D. (1996): Statistics: Concepts and Controversies (4ª ed.). Ed. W.H. Freeman and Company.
MURES, MªJ. (2003): Problemas de Estadística Descriptiva aplicada a las Ciencias Sociales. Ed. Prentice Hall.
PÉREZ, R.; LÓPEZ, A.J.; RÍO, M.J.; MUÑOZ, N.; CASO, C.; ALVARGONZÁLEZ, M. y J.B. GARCÍA (1997): Análisis de datos económicos I. Métodos descriptivos. Ed. Pirámide.
URIEL, E. y M. MUÑIZ (1993): Estadística Económica y Empresarial. Teoría y Ejercicios. Ed. AC.
Worksheet references
ARNALDOS, F.; DÍAZ, M.T.; FAURA, U.; MOLERA, L.; PARRA, I. (2003): Estadística Descriptiva para Economía y Administración de Empresas. Editorial AC.
GLYN, D. and P. BRANKO (2010): Business Statistics using Excel. Ed. Oxford.
Websites
Institution | Web |
National Statistics Institute (INE) | http://www.ine.es |
Statistical Office of the European Union (EUROSTAT) | http://ec.europa.eu/eurostat |
Sociedad Asturiana de Estudios Económicos e Industriales (SADEI) | http://www.sadei.es |
Bank of Spain | http://www.bde.es |
Software
Sessions in the computer lab will be conducted using Excel spreadsheet (Microsoft Office).