Teaching plan for the course unit



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General information


Course unit name: Quantitative Analysis Applied to International Business

Course unit code: 573238

Academic year: 2021-2022

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



-  Lecture with practical component





-  Problem-solving class




Supervised project


Independent learning




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.


CG1. Creative and entrepreneurial skills (capacity to conceive, design and manage projects, and to research and integrate new knowledge and approaches).





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 explain the basic concepts of each teaching unit in class and provide students with materials that allow them to carry out independent 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, 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 main activity consists of a set of tasks detailed at the beginning of the course, worth 100% 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 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.

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.


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 final examination worth 100% of the final grade. The date of the examination is set by the Academic Council. This examination consists of several questions on the theory and practical aspects of the course.

Students who fail to pass the course (either through continuous or single assessment) have the option of a repeat examination with the same characteristics as the one in single assessment.



Reading and study resources

Consulteu la disponibilitat a CERCABIB


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

Catāleg UB. Versiķ en castellā (2013)  Enllaç

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

Catāleg UB  Enllaç

Daniel Peña: Fundamentos de Estadística. Alianza Editorial, 2014

Catāleg UB   Enllaç