General information

Subject type: Mandatory

Coordinator: Monica Juliana Oviedo León

Trimester: Third term

Credits: 4

Teaching staff: 

Roberto Dopeso Fernandez
Jose Ignacio Monreal Galán 


Basic skills
  • CB2. That students know how to apply their knowledge to their work or vocation in a professional way and possess the skills that are usually demonstrated through the elaboration and defense of arguments and the resolution of problems within their area of ​​study. .

  • CB3. That students have the ability to gather and interpret relevant data (usually within their area of ​​study) to make judgments that include reflection on relevant social, scientific, or ethical issues.

Specific skills
  • CE13. Identify the basic tools of e-Marketing.

  • CE15. Gather and interpret meaningful data to make judgments that include reflection on relevant business issues and be able to prepare a document that allows for the transmission of information or an innovative business proposal.

  • CE3. Identify the qualitative and quantitative tools of analysis and diagnosis for market research.

General competencies
  • CG1. Be able to work in a team, actively participate in tasks and negotiate in the face of dissenting opinions until reaching consensus positions, thus acquiring the ability to learn together with other team members and create new knowledge.

Transversal competences
  • CT4. Master computer tools and their main applications for ordinary academic and professional activity.

  • CT5. Develop tasks applying the knowledge acquired with flexibility and creativity and adapting them to new contexts and situations.


Fundamental analysis tools within the scope of a Strategic Marketing Plan, through the application of metrics that serve as support in the company's decision-making and in the application of management indicators. Study of the instruments of descriptive statistics to organize, summarize, deepen and present the information coming from secondary or own sources and to make inference by means of the same.

Learning outcomes

Understand and apply the basic concepts of statistical probability and inference, basic statistical calculations and the computer tools that facilitate them.

Working methodology

Theoretical sessions
MD1.Master class: Expository class sessions based on the teacher's explanation attended by all students enrolled in the subject
MD3. Presentations: Multimedia formats that support face-to-face classes

Guided learning
MD5. Seminars: Face-to-face format in small work groups (between 14 and 40). These are sessions linked to the face-to-face sessions of the subject that allow to offer a practical perspective of the subject and in which the participation of the student is key.
MD6. Debates and forums: Face-to-face or online conversations, according to the objectives that the teacher responsible for the subject pursues. 
MD7. Case study: Dynamics that starts from the study of a case, which serves to contextualize the student in a specific situation, the teacher can propose different activities, both individually and in groups, among their students

Autonomous learning
MD9. Solving exercises and problems: Non-contact activity dedicated to solving practical exercises based on the data provided by the teacher
MD10. Research and critical reading of articles. Students start from a working hypothesis that they will develop, following the phases of the research methodology, including the critical reading of articles.

This subject has methodological and digital resources to make possible its continuity in non-contact mode in the case of being necessary for reasons related to the Covid-19. In this way, the achievement of the same knowledge and skills that are specified in this teaching plan will be ensured. The TecnoCampus will make available to teachers and students the digital tools needed to carry out the course, as well as guides and recommendations that facilitate adaptation to the non-contact mode.

 The classroom (physical or virtual) is a safe space, free of sexist, racist, homophobic, transphobic and discriminatory attitudes, either towards students or teachers. We trust that together we can create a safe space where we can make mistakes and learn without having to suffer the prejudices of others.


Topic 1

  • Introduction
    • What are and why are marketing metrics important?
    • What is statistical inference.

Topic 2

  • Metrics in marketing.
    • Basic metrics.
    • Web and social media metrics.

Topic 3

  • Estimation of population parameters
    • Distribution of the mean of random variables: Central Limit Theorem.
    • Punctual estimation of the population average.
    • Punctual estimation of the population proportion.
  • Confidence intervals of population parameters
    • Standard error. Estimation by intervals. Confidence level. Estimation error.
    • Confidence intervals of the population average.
    • Confidence intervals of population proportion.
    • Confidence intervals of the difference in population averages.
    • Confidence intervals of the difference in population proportions
  • The sample size
    • Relationship between sample size and estimation error.
    • Calculation of sample size to estimate the mean or population proportion.

Topic 4

  • Contrast of statistical hypotheses
    • Concepts of null hypothesis and alternative hypothesis. Significance level, Type I error (alpha), Type II error (beta). P-value. Critical value. Zone of rejection of the null hypothesis.
    • Contrast of the population average.
    • Contrast of the population proportion.
    • Contrast the difference in population means for independent samples.
    • Contrast the difference in population proportions for independent samples

Topic 5

  • Analysis of variance to a factor
    • Comparison of more than two population averages.
    • Analysis of variance (ANOVA).
  • Contingency Tables
    • Attribute independence test.
    • The Ji-Square distribution.

Topic 6

  • Multivariate analysis (I)
    • Regression Analysis
    • Factor analysis
    • Cluster analysis

Learning activities

AF1. Theoretical sessions
AF3. Work in group
AF4. Individual work
AF5. Personal study
AF10. Search, read and prepare reviews / text comments on bibliography / information through ICT / virtual platform.

Evaluation system

- SE2. Individual and Group Work 30% (Theoretical Exercises within each topic)

- SE5. (Portfolio), SE3 (Presentations and Exhibitions) 10% (Case Studies, Reading Control, Presentation of the results of the Group Exercises, Discussion of Articles and Class Participation)

- SE4. 60% Final Exam

To pass the course you must obtain a grade equal to or higher than 4/10 in the final exam, and that the average of the continuous assessment and the exam is higher than 5/10.

There will be a recovery at the end of the quarter. Only the Final Exam grade will be recovered, so 40% of the grade is unrecoverable.



Farris, Paul W., Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein (2015). Marketing Metrics: The Definitive Guide to Measuring Marketing Performance. 3rd ed. Pearson Education.

Kachigan (1991), Multivariate Statistical Analysis, A conceptual introduction, 2nd ed. Radius Press

Kohler, U. and Kreuter, F. (2012) Data Analysis Using State, Third Edition, State Press


Lind, DA; Marchal, WG; Wathen, SA, et. at the. (2012) Statistics applied to business and the economy, 15ª ed. Mc Graw Hill.

Doncel, Alejandro Domínguez, and Gemma Muñoz Vera (2010). Marketing Metrics. Pozuelo De Alarcón (Madrid): ESIC.

J., Arriaza Gómez A. et. At the. (2008) Basic Statistics With RY R-Commander. Cádiz: Universidad De Cádiz, Servicio De Publicaciones.