Checking date: 23/08/2018


Course: 2018/2019

Data analytical techniques for business
(13475)
Bachelor in Business Administration (Plan: 395 - Estudio: 204)


Coordinating teacher: VELILLA CERDAN, SANTIAGO

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Sequences: Statistics I-II Mathematics for Economics I-II In general: Fundamentals of Statistics, Linear Algebra, and Mathematical Analysis.
Knowledge of basic statistical techniques of Data Analysis Use of Statistical software for Data Analysis , in particular MIcrosoft Excel
Description of contents: programme
The purpose of the course is to present an introduction to Data Analytical Techniques at an intermediate level. Emphasis is mainly in applications and examples, not in theoretical derivations. The course requires the intensive use of computer software, specially Microsoft Excel. Prerequisites are some solid knowledge of Matrix Algebra, as well as good foundations of Statistics. ************** DATA ANALYTICAL TECHNIQUES FOR BUSINESS *************** 1. REVIEW of elements of Statistics ** 1.1 Basic concepts ** 1.2 Notation ** 1.3 Data examples 2. FUNDAMENTALS of Statistical Software ** 2.1 Editing text and Excel files ** 2.2 Importing text data into Excel ** 2.3 Constructing compressed data files ** 2.4 Defining ranges in Excel ** 2.5 Excel functions and expressions ** 2.6 Matrices with Excel ** 2.7 Excel charts ** 2.8 Pivot Tables ** 2.9 Conditional formatting ** 2.10 Excel Add-Ins 3. MULTIDIMENSIONAL data ** 3.1 The data matrix ** 3.2 Different types of data ** 3.3 Mean vector ** 3.4 Covariance and correlation matrices ** 3.5 Graphical methods ** 3.6 Linear combinations ** 3.7 Applications with Excel 4. PRINCIPAL components ** 4.1 Motivation and construction ** 4.2 Standardized case ** 4.3 Data examples ** 4.4 Applications with Excel 5. POPULATION concepts and sampling ** 5.1 Random vectors ** 5.2 Expected values ** 5.3 The univariate and multivariate normal distributions ** 5.4 Sampling distributions 6. SIMULATION techniques ** 6.1 Generation of univariate and multivariate normal data ** 6.2 Applications and examples with Excel 7. CASE analysis ** 7.1 Examples of real data applications in Business, Economics, Finance and Marketing
Learning activities and methodology
Competences will be acquired by students from: [I] Theory classes: one per week (14 sessions) [II] Practical classes in the computer room: one per week (14 sessions) Activities [I] and [II] will be devoted to exercises, problems, data examples, and case studies. Teaching will make intensive use of resources available in Aula Global.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Basic Bibliography
  • ALBRIGHT, S. C. y WINSTON, W. L. . Business Analytics: Data Analysis & Decision Making, 6th Edition. Cengage Learning. 2017
  • JOHNSON, R.A. y WICHERN, D.W.. Applied Multivariate Statistical Analysis, 6th Edition. Prentice Hall. 2007
Additional Bibliography
  • ANDERSON, D. R., SWEENEY, D. J. y WILLIAMS, T. A. . Essentials of Modern Business Statistics with Microsoft Excel, 6th Edition. Cengage Learning. 2016
  • WINSTON, WAYNE L.. Microsoft Excel 2016: Data Analysis and Business Modeling, 5th Edn. Microsoft Press. 2016

The course syllabus may change due academic events or other reasons.