General information

Subject type: Basic

Coordinator: Monica Juliana Oviedo León

Trimester: First term

Credits: 6

Teaching staff: 

Jose Maria Raya Vilchez
Catherine Llaneza Hesse 
Laura Muñoz Ortiz 

Teaching languages

  • Catalan
  • Spanish
  • English

There may be materials in English and Catalan.


Basic skills
  • B5. That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy.

Specific skills
  • E15. 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.

  • E3. Identify the qualitative and quantitative tools of analysis and diagnosis for market research.

General competencies
  • G1. 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
  • T4. Master computer tools and their main applications for ordinary academic and professional activity.

  • T5. Develop tasks applying the knowledge acquired with flexibility and creativity and adapting them to new contexts and situations.


• Apply qualitative and quantitative statistical techniques for market research
• Plan, organize, carry out and present a market research project and use the results obtained for decision making

Ability to recognize, become familiar with and use statistical techniques when making market decisions. All this approach will make compatible the ability to manually calculate the various tools for a small set of data with the ability to use and analyze and interpret the outputs of statistical software. Some questions that will be solved throughout the course:

  • How do you know what the most profitable action is? And the riskiest?
  • Which action presents a more symmetrical price distribution?
  • Can we know the profitability of a year of education?
  • How do we know which company spends the most on advertising? Are sales and advertising associated?
  • How much does the price of a home in Barcelona increase by increasing its area by one square meter?
  • Can we criticize the housing price index made by the Ministry of Housing?
  • How could we build an index of the evolution of the price of housing that takes into account that the homes that are sold every year are not the same?
  • How much is the seasonal effect of August for the entry of tourists into Catalonia?
  • What is the expected value that an entrepreneur will get when deciding whether or not to raise the price?
  • How is the probability that an individual is in the upper income bracket of personal income tax if we know that income in Spain follows a certain normal distribution?
  • What can we extract from the analysis of a customer text?


Learning outcomes

Be able to describe the distribution of a variable at all levels: centralization, dispersion, symmetry and kurtosis (such as the number of followers of various twitter profiles)

Identify the strength of the association between variables.

Differentiate between correlation and causality

Quantify the causal relationship between two variables such as advertising and sales

Identify the different patterns in a time series (trend and seasonality) such as visitors to a web page

Calculate probabilities in a situation of uncertainty for the most common distributions.

Working methodology

  • MD1. Master class
  • MD2. Conferences
  • MD5. Seminars
  • MD7. Case studies
  • MD9. Solving exercises and problems

The face-to-face sessions with the whole group will combine theory sessions with hand-held exercise resolution sessions and through case studies with data from real companies.

In the practical sessions students will work on exercises and databases with the R / Stata program (to be determined). You will need to bring a laptop to the classroom.

There will be a lecture by a professional who uses Statistics applied to Marketing. Whether in market research, big data or strategic positioning.

 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



  • Basic concepts: population, sample, sampling type, variables, variable types, data and data types. Text mining.

Topic 2

One-dimensional statistics

  • Centralization measures
  • Dispersion measures
  • Symmetry measurements
  • Measures of kurtosis
  • Case 1: marketing company

Topic 3

Two-dimensional statistics

  • Association of quantitative variables: linear regression
  • Association of qualitative variables
  • Case 2: relationship between sales and advertising

Topic 4

Time series

  • Components of a time series
  • Seasonalization of a time series
  • Case 3: Sales series analysis

Topic 5


  • Basics
  • Discrete distributions: binomial distribution
  • Continuous distributions: normal distribution

Learning activities

  • AF1. Theoretical sessions
  • AF2. Seminars
  • AF3. Work in group
  • AF4. Individual work
  • AF5. Personal study


Exercise Descriptive statistics. Individual (Inside and outside the classroom)

Descriptive statistical test. Individual (Inside and outside the classroom). Virtual

Exercise association between quantitative variables. Individual (Inside and outside the classroom)

Exercise association between qualitative variables. Individual (Inside and outside the classroom)

Exercise of time series. Individual (Inside and outside the classroom)

Association test between quantitative and qualitative variables and time series. (In and out of the classroom). Virtual

Binomial distribution exercise. Individual (Inside and outside the classroom)

Normal distribution exercise. Individual (Inside and outside the classroom)

Probability test. (In and out of the classroom). Virtual

Work with computer software. Group (Inside and shape of the classroom)

Exam. Individual


Evaluation system

The quarterly evaluation will take into account the following aspects with the weights indicated:
- SE4. Final exam of term: 60%. Minimum grade 3.5 out of 10.
- SE2. Database work: 30%
- SE2. Delivery of exercises and proposed practices: 10% 

There will be a recovery at the start of the next quarter. Only the exam will be retaken. The other 40% will maintain the quarterly assessment mark.

A student who has not applied for the first call CANNOT apply for recovery.



RAYA, J. (2012): Statistics applied to business and marketing. Prentice Hall

SPIEGELHALTER, D. (2019). The Art of Statistics: Learning from Data. Pelican books. 


NEWBOLD, PAUL, Carlson, W., Thorne, W. (2007), Statistics for Business and the Economy, 6th edition, Madrid, Prentice Hall.