Name: QUANTITATIVE AND COMPUTING TOOLS FOR BUSINESS DECISION MAKING
Code: 212101005
Type: Compulsory
ECTS: 4
Length of subject: Per term
Semester and course: 1st Year - First term
Speciality:
Language: English
Mode of study: On-site class
Lecturer data: GARCÍA CÓRDOBA, JOSÉ ANTONIO
Knowledge area: Métodos Cuantitativos para la Economía y Empresa
Department: Métodos Cuantitativos, Ciencias Jurídicas y Lenguas Modernas
Telephone:
Email: josea.garcia@upct.es
Office hours and location: Contact with the lecturer
Qualifications/Degrees:
Graduate in Degree in Business Administration and Management from UNED (SPAIN) - 2017
PhD in ECONOMY AND BUSINESS MANGEMENT from Technical University of Cartagena (SPAIN) - 2004
Master in MBA from IE BUSINESS SCHOOL (SPAIN) - 1989
Licensed in MATHEMATICS from University of Granada (SPAIN) - 1985
Academic rank in UPCT: Profesor Contratado Doctor
Number of five-year periods: 1
Number of six-year periods: 0
Curriculum Vitae: Full Profile
Lecturer data: COBACHO TORNEL, MARÍA BELÉN
Knowledge area: Métodos Cuantitativos para la Economía y Empresa
Department: Métodos Cuantitativos, Ciencias Jurídicas y Lenguas Modernas
Telephone: 968325402
Email: belen.cobacho@upct.es
Office hours and location: Contact with the lecturer
Qualifications/Degrees:
Academic rank in UPCT: Profesora Titular de Universidad
Number of five-year periods: 4
Number of six-year periods: 1 de investigación
Curriculum Vitae: Full Profile
[CB10 ]. Students are required to have the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous.
[01 ]. To be able to apply the knowledge acquired and to have the ability to solve problems in new environments, within broader (or multidisciplinary) contexts related to the company, public administration and the free practice of the profession.
[04 ]. To acquire skills in the teaching-learning process which allow them to continue training and learning in their particular field, both through established contacts with professors and professionals of the Master and in an autonomous way.
[25 ]. To understand and be able to use the necessary tools to continue with an autonomous process in the activities of management and business management, public administration and the free exercise of the profession.
[CT3 ]. Learning in an autonomous way
1. Be able to apply quantitative and computing tools to the analysis of economic and business data and to decision making.
2. Be able to create models for analysis, planning and business simulation with spreadsheets.
3. Be able to identify business behaviour patterns using statistical techniques.
4. Be able to apply optimization techniques in business.
5. Be able to create and present reports by using quantitative and computing tools.
Computing, statistical and operations research tools to create models for data analysis and decision making in business. Creating and programming real model with spreadsheets based on quantitative techniques, to analyse economic business data, planning and simulation, as a support for decision making in economics, industry and businesses. Principal components and cluster analysis applied to economic and business data. Techniques and models for planning, optimization and decision making in businesses by using specific software.
UNIT ONE1: STATISTICAL TOOLS
1. Basic exploratory analysis. Graphics
2. Design and elaboration of bidimensional tables.
3. Multiple linear regression. Validation of structural hypotheses.
4. Principal component analysis.
5. Binary logistic regression.
6. Cluster analysis.
7. Exploratory analysis of spatially referenced data (extra content).
UNIT TWO: OPERATIONAL RESEARCH TOOLS.
8. Applications of Operations Research in business management.
Statistical tools
Excel, SPSS, R, Jamovi
Operations research tools
WinQSB
Promoting the continuous improvement of working and study conditions of the entire university community is one the basic principles and goals of the Universidad Politécnica de Cartagena. Such commitment to prevention and the responsibilities arising from it concern all realms of the university: governing bodies, management team, teaching and research staff, administrative and service staff and students. The UPCT Service of Occupational Hazards (Servicio de Prevención de Riesgos Laborales de la UPCT) has published a "Risk Prevention Manual for new students" (Manual de acogida al estudiante en materia de prevención de riesgos), which may be downloaded from the e-learning platform ("Aula Virtual"), with instructions and recommendations on how to act properly, from the point of view of prevention (safety, ergonomics, etc.), when developing any type of activity at the University. You will also find recommendations on how to proceed in an emergency or if an incident occurs. Particularly when carrying out training practices in laboratories, workshops or field work, you must follow all your teacher's instructions, because he/she is the person responsible for your safety and health during practice performance. Feel free to ask any questions you may have and do not put your safety or that of your classmates at risk.
Theory class: Activities consisting of training sessions to develop theoretical knowledge based on concepts and theories
Expository class using the method of the lesson and the case method. Resolution of questions raised by the students. They will be divided into three parts: Computing, Statistics and Operations Research. This activity contributes to competences 4, 25 and CB10 and learning outcomes 1, 4 and 5.
9
100
Problem solving class: Activities consisting of training sessions to develop practical or applied knowledge based on problem solving exercises, or practical cases
0
100
Laboratory or field practice class: Activities aimed at developing practical or applied skills by the student supervised by a remote teacher
Practical class in the computer classroom, where a problem is proposed giving time for its resolution. Resolution of questions raised by the students. They will be divided into three parts: Computing, Statistics and Operations Research. This activity contributes to competences 1 and 25 and learning outcomes 2, 3 and 4.
28
100
Practical class in the computer room: Activities for the acquisition of certain skills through the use of specific software
0
100
Seminars, tutorials led by teaching staff, conferences, visits, round tables, etc .: Activities to develop theoretical, practical or applied knowledge based on specific topics or views of the profession
Exposition by students of their project. This activity contributes to competence 1 and learning outcome 5.
0
100
Assessments (continuous assessment system): speaking or writing tests, presentations, individually or in groups, which should include the knowledge acquired in the classes. Formative and summative assessment activities are included here
oral or written exams during the course
3
100
Assessments (final assessment system): speaking or writing tests, individually or in groups, which should include the knowledge acquired in the classes. Summative evaluation is included
final exam to assess the adquired knowledge
3
100
Tutorials: Individual or in groups, will serve to advise, resolve any doubts, guide, monitor work or the knowledge acquired
Answering questions about theory and problems solving. This activity contributes to the CB10 competence and all learning outcomes.
3
50
Carrying out individual or group assignments: Autonomous and / or collaborative learning to develop theoretical, practical or applied knowledge by carrying out projects, practice reports and / or assignments
development of a project. This activity contributes to CB10 and CT3 competences and all learning outcomes.
34
0
Individual study: Time dedicated to studying the subject
Autonomous study of the subject
20
0
Exam
Practical questions to be solved by students in the computer classroom. The exam could be divided into the parts that compose the subject: Computer Science, Statistics and Operational Research. This activity contributes to the assessment of competencies 1 and 25 and all learning outcomes.
40 %
Attendance and participation
Active participation and exercises during the theoretical and practical classes. This activity contributes to the evaluation of competencies 4 and CB10 and all learning outcomes.
10 %
Individual assignment
Elaboration of works, practical exercises or reports, which may be divided into the parts that compose the subject: Computer Science, Statistics and Operations Research. This activity contributes to evaluate the competences 1, 25 and TC3, as well as all the learning results.
50 %
Exam
Practical questions in the computer classroom
50 %
Individual assignment
Submission of practical exercises or projects and reports
50 %
IN THE FINAL EVALUATION SYSTEM, THE PERCENTAGE OF THE EVALUATION CORRESPONDING TO CLASS ATTENDANCE AND PARTICIPATION IN THE CONTINUOUS EVALUATION SYSTEM IS ADDED TO THE EVALUATION OF THE EXAM.
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