Teaching plan for the course unit

 

 

Close imatge de maquetació

 

Print

 

On 3 April 2020 and in agreement with the President of the Government of Catalonia, the Catalan Minister of Business and Knowledge and the rectors of the other Catalan universities, the Rector of the Universitat de Barcelona decided to suspend all second-semester face-to-face teaching activities until the end of the academic year. For this reason, our university's teaching staff may need to make certain changes to the course plans of the subjects they teach, so that they can teach subjects online. When and where such changes are made, they will be explained in a new appendix attached to the end of the original course plan.



General information

 

Course unit name: Quantitative Analysis Applied to International Business

Course unit code: 573238

Academic year: 2019-2020

Coordinator: Javier Manuel Romani Fernandez

Department: Faculty of Economics and Business

Credits: 2,5

Single program: S

 

 

Estimated learning time

Total number of hours 62.5

 

Face-to-face and/or online activities

26

 

-  Lecture with practical component

Face-to-face

 

19.5

 

-  Problem-solving class

Face-to-face

 

6.5

Supervised project

18

Independent learning

18.5

 

 

Competences to be gained during study

 

CB7. Capacity to apply the acquired knowledge to problem-solving in new or relatively unknown environments within broader (or multidisciplinary) contexts related to the field of study.

 

CB8. Capacity to integrate knowledge and tackle the complexity of formulating judgments based on incomplete or limited information, taking due consideration of the social and ethical responsibilities involved in applying knowledge and making judgments.

 

CB9. Capacity to communicate conclusions, judgments and the grounds on which they have been reached to specialist and non-specialist audiences in a clear and unambiguous manner.

 

CB10. Skills to enable lifelong self-directed and independent learning.

 

CE5. Understanding of and capacity to apply marketing tools to solve problems and generate opportunities and to use theoretical expertise and the appropriate research tools to solve problems encountered in the fields of market research and international marketing.

 

CE6. Understanding of the heuristics, methodologies and techniques required for decision-making in the field of international business operations.

 

CE10. Capacity to acquire an advanced level of competence in the writing of scientific documents, specialized reports and research papers in which value judgements are formulated, complying with standard criteria for publication or for presentation to potential stakeholders or other interested parties at the global level.

 

 

 

 

Learning objectives

 

Referring to knowledge

— Distinguish among different types of quantitative data (categorical, continue, etc.) and recognise the type of information they provide, as well as their limitations.

 

— Recognise the main types of distribution, how they interact with available data and how to use them in statistical analysis.

 

— Infer the characteristics of the population from samples.

 

— Recognise the key characteristics of statistical tests (significance, power, confidence intervals) and run statistical tests on data.

 

— Understand the concepts of correlation, partial correlation, simple and multivariate regression.

 

— Generate and interpret the results obtained using the existing software.

 

— Discuss and recommend solutions to problems detected in the analysis of a specific phenomenon.

 

— Inform and interpret the results of the analyses in a clean and effective way for readers with no technical knowledge on statistics and econometrics.

 

— Make recommendations based on the results of the analysis.

 

 

Teaching blocks

 

1. The concept and content of statistics

*  1.1. The goal of statistics
1.2. Descriptive statistics and statistical inference
1.3. Population and samples
1.4. Data; Classification and scales of measurement
1.5. Statistical sources

2. One-dimensional frequency distribution and graphic representation

*  2.1. Frequency distributions
2.2. Graphic representations
2.3. Exploratory data analysis: stem-and-leaf plot

3. Measures of position

*  3.1. Arithmetic mean, median and mode
3.2. Properties
3.3. Measures of location: quantiles

4. Measures of dispersion and shape

*  4.1. Dispersion: box plots
4.2. Variance and standard deviation
4.3. Linear transformations: standardised variables
4.4. Measures of shape

5. Two-dimensional frequency distribution

*  5.1. Joint frequency distributions; Marginal distribution
5.2. Conditional distribution
5.3. Statistical independence
5.4. Contingency tables: association between attributes

6. Association between variables

*  6.1. Scatter plots
6.2. Linear association: covariance
6.3. Pearson’s correlation coefficient
6.4. Linear regression

7. One-dimensional random variables

*  7.1. Random variable: discrete, continuous
7.2. Probability distribution: quantity function and density function
7.3. Distribution function
7.4. Mathematical expectation and variance; Standardised variable

8. One-dimensional probability distribution

*  8.1. Dichotomous and binomial distribution
8.2. Normal distribution

9. Distribution models for random variables

*  9.1. Distribution models for discrete and continuous random variables
9.2. Distributions derived from normal distribution
9.3. Convergence: central limit theorem

10. Elements of sampling theory

*  10.1. Basic concepts: random and statistical samples
10.2. Distribution of some statistics in a sample

11. Point estimation

*  11.1. Introduction to the estimation process
11.2. Properties of point estimates
11.3. Methods of point estimation

12. Interval estimation

*  12.1. Definition of confidence intervals
12.2. Confidence intervals for sample means and mean differences
12.3. Confidence intervals for proportions and differences between proportions
12.4. Confidence intervals for variances
12.5. Choosing sample size

13. Contrasts of statistical hypotheses

*  13.1. Basic concepts: critical regions
13.2. Types of errors; The power of a contrast
13.3. Means testing and equality of means
13.4. Analysis of variance and equality of variances
13.5. Test of proportions and equality of proportions

14. Chi-square tests

*  14.1. Goodness of fit tests
14.2. Test of independence

 

 

Teaching methods and general organization

 

Lecturers expose the basics of each teaching unit in class, and provide students with materials that allow them to carry out autonomous learning. The key aspects are later discussed in class. Students are therefore encouraged to actively participate in these discussions. In addition, some practical lessons take place in the computer room through the use of software for data analysis, in order to learn about the practical implementation of theory concepts, analyse the results and understand them.

 

 

Official assessment of learning outcomes

 

Continuous assessment consists of:

— The first activity consists of a set of tasks detailed at the beginning of the course, worth 40% of the final grade. For example, students may choose a topic of interest for research in the business field and complete the assignment as the theoretical contents necessary for every stage are explained in class. This activity is always carried out by providing the necessary feedback between the lecturer and students. Finally, students obtain a database that can support the application of the statistical techniques presented during the last lessons of the course.

— A final examination set by the Academic Committee within the standard assessment period, worth the remaining 60% of the final grade. The examination contains multiple-choice questions on the theory and practical content of the course.

For the marks for continuous assessment tasks and the examination to be considered in the calculation of the final grade, students must complete a minimum of 80% of class exercises and obtain a mark of at least 3.5 in the final examination. Otherwise, they are automatically entered for single assessment.

 

Examination-based assessment

Students who do not wish to be assessed on a continuous basis are entered for single assessment, which consists of a single end-of-semester examination worth 100% of the final grade. The date of the examination is set by the Academic Committee. This examination consists of several questions on the theory and practical aspects of the course.

 

 

Reading and study resources

Consulteu la disponibilitat a CERCABIB

Book

Paul Newbold, William L. Carlson, Betty M. Thorne: Statistics for business and economics. 8th Edition. Pearson Education, 2013.

Douglas A. Lind, William G. Marchal, Samuel A.Wathen: Basic statistics for business and economics, 8th Edition. McGraw-Hill, 2013.

Daniel Peña: Fundamentos de Estadística. Alianza Editorial, 2014

 

 

ADAPTATION OF THE COURSE PLAN TO ONLINE TEACHING MODE FOR THE REMAINDER OF THE ACADEMIC YEAR 2019-2020, IN RESPONSE TO THE COVID-19 CRISIS

 

Metodologia i activitats formatives alternatives:

La docencia ya estaba muy avanzada en el momento de finalización de las clases presenciales. Para los temas que faltaban se han habilitado materiales, tales como presentaciones visuales y ejemplos y ejercicios resueltos y comentados por el profesor. También se ha habilitado un foro específico de dudas y preguntas en el Campus Virtual.

 

AVALUACIÓ CONTINUADA

Los alumnos pueden optar en cualquier momento por la evaluación única mediante el envío de un correo electrónico al profesor en el que expresen explícitamente su renuncia a la evaluación continua. Para los alumnos que opten por la evaluación continua, el método de evaluación será la realización de un Trabajo, en el que el profesor les proporcionará los datos (que serán individualizados para cada alumno), y los estudiantes deben analizar dichos datos utilizando las técnicas aprendidas durante el curso e interpretar los resultados obtenidos.

 

AVALUACIÓ ÚNICA

Se realizará un examen en una hora concreta y con un tiempo máximo determinado. El enunciado del examen estará disponible en el Campus Virtual a partir de la hora de comienzo del examen, y las respuestas deberán enviarse al Campus Virtual antes de la hora de finalización.

 

REAVALUACIÓ

Se evaluaría mediante un examen on-line de características similares a la prueba de evaluación única.