General information 
Course unit name: Anàlisi Quantitativa Aplicada a l'Empresa Internacional
Course unit code: 573238
Academic year: 20182019
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 
Facetoface learning activities 
26 
 Lecture with practical component 
19,5 

 Problemsolving class 
6,5 
Supervised project 
18 
Independent learning 
18,5 
Competences to be gained during study 
CB7 Capacity to apply the acquired knowledge to problemsolving 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 nonspecialist audiences in a clear and unambiguous manner.

CB10 Skills to enable lifelong selfdirected 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 decisionmaking 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 To distinguish among different types of quantitative data (categorical, continue, etc.) and recognize the types of information they provide, as well as their limitations
To recognize the main types of distribution, how they interact with available data and how could they be used in the statistical analysis
To infer about the characteristics of the population based on the samples
To recognize the key characteristics of the statistical tests (significance, power, confidence intervals) and to realize statistical tests on data
To understand the concepts of correlation, partial correlation, simple and multivariate regression
To generate and interpret the results obtained using the existing software
To discuss and recommend solutions to problems detected in the analysis of an specific phenomenon
To inform and interpret the results of the analysis in a clean and effective way for a reader with no technical knowledge on statistics and econometrics
To make recommendations based on the results of the analysis 
Teaching blocks 
1. 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. 2. Onedimensional frequency distribution and graphic representation
* 2.1. Frequency distributions
2.2. Graphic representations
2.3. Exploratory data analysis: Stemandleaf plot
3. 3. Measures of position
* 3.1. Arithmetic mean, median and mode
3.2. Properties
3.3. Measures of location: Quantiles
4. 4. Measures of dispersion and shape
* 4.1. Dispersion: Box plots
4.2. Variance and standard deviation
4.3. Linear transformations: Standardized variables
4.4. Measures of shape
5.
5. Twodimensional 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. 6. Association between variables
* 6.1. Scatter plots
6.2. Linear association: Covariance
6.3. Pearson’s correlation coefficient
6.4. Linear regression
7. 7. Introduction to probability theory
* 7.1. Random experimentation; Probability: Axiomatic and properties
7.2. Conditional probability
7.3. Intersection theorem: Independence of events
7.4. Total probability theorem; Bayes’ theorem
8. 8. Onedimensional random variables
* 8.1. Random variable: Discrete, continuous
8.2. Probability distribution: Quantity function and density function
8.3. Distribution function
8.4. Mathematical expectation and variance; Standardized variable
9. 9. Onedimensional probability distribution
* 9.1. Dichotomous and binomial distribution
9.2. Normal distribution
10. 10. Distribution models for random variables
* 10.1. Distribution models for discrete and continuous random variables
10.2. Distributions derived from normal distribution
10.3. Convergence: Central limit theorem
11. 11. Elements of sampling theory
* 11.1. Basic concepts: Random and statistical samples
11.2. Distribution of some statistics in a sample
12. 12. Point estimation
* 12.1. Introduction to the estimation process
12.2. Properties of point estimators
12.3. Methods of point estimation
13. 13. Interval estimation
* 13.1. Definition of confidence intervals
13.2. Confidence intervals for sample means and mean differences
13.3. Confidence intervals for proportions and proportion differences
13.4. Confidence intervals for variance
13.5. Choosing sample size
14. 14. Contrasts of statistical hypotheses
* 14.1. Basic concepts: Critical regions
14.2. Types of errors; The power of a contrast
14.3. Means testing and equality of means
14.4. Variance testing and equality of variance
14.5. Proportions testing and equality of proportions
15. 15. Chisquare tests
* 15.1. Goodness of fit test
15.2. Test of independence
Teaching methods and general organization 
The teacher exposes in class the basics of each subject, and provides the student with material so that he can carry out autonomous learning. In the classroom, the key aspects are discussed later, so that a participatory attitude of the students is encouraged. In addition, some practical lessons will take place in the computer room using software for data analysis, in order to learn the practical implementation of the theoretical concepts, analyze the results and understand them. 
Official assessment of learning outcomes 
Continuous assessment consists of:
Examinationbased assessment Examinationbased assessment
Students who do not wish to be assessed on a continuous basis are entered for single assessment, which consists of an endofsemester examination worth 100% of the final grade for the subject. The examination date is set by the Academic Council. This examination consists of several questions on the theoretical and practical aspects of the course content. 
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. McGrawHill, 2013.
Daniel Peña: Fundamentos de Estadística. Alianza Editorial, 2014