TecnoCampus Foundation
eCampus
University Business
eCampus

What are you looking for?

General information

Subject type: Basic

Coordinator: Núria Masferrer Llabinés

Trimester: First term

Credits: 6

Teaching staff: 

Jose Maria Raya Vilchez
Catherine Llaneza Hesse 

Teaching languages

  • Catalan
  • Spanish
  • English

There may be materials in English and Catalan.

Skills

Basic skills

  • B3_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

     

  • B5_That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy

Specific skills

  • E9_Use mathematical tools and advanced statistical tools for decision making and contrasting various economic assumptions

     

General competencies

  • G1_Be able to work in a team, actively participating in tasks and negotiating dissenting opinions until reaching consensus positions, thus acquiring the ability to learn together with other team members and create new knowledge

Transversal competences

  • T4_Domain the computer tools and their main applications for the ordinary academic and professional activity

Description

• 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?

 

Contents

Topic 1

 

Introduction

  • 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

Probability

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

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.

REFERENCES

Basic

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

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

Complementary

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