Name: BUSINESS STATISTICS I
Code: 510101004
Type: Basic
ECTS: 7.5
Length of subject: Yearly
Semester and course: 1st Year - Yearly
Speciality:
Language: English
Mode of study: On-site class
Lecturer data: RUIZ MARÍN, MANUEL
Knowledge area: Métodos Cuantitativos para la Economía y Empresa
Department: Métodos Cuantitativos, Ciencias Jurídicas y Lenguas Modernas
Telephone: 968325901
Email: manuel.ruiz@upct.es
Office hours and location:
Qualifications/Degrees:
Academic rank in UPCT: Catedrático de Universidad
Number of five-year periods: 4
Number of six-year periods: 3 de investigación
Curriculum Vitae: Full Profile
[CB3 ]. Students are required to have the ability to gather and interpret relevant data (usually within their area of study) to make judgments that include a reflection on relevant issues of a social, scientific or ethical nature.
[CG2 ]. To apply mathematical-statistical methods and information and communication technologies to the treatment, assessment, and forecasting of economic-business information.
[CE04 ]. To reasonably describe the behavior of qualitative and quantitative data with the help of statistical techniques.
[CT4 ]. Using information resources responsibly
Utilizar diferentes técnicas del análisis descriptivo de datos
Ordenar la recogida, organización y análisis descriptivo datos
Argumentar y tomar decisiones basándose en el análisis de la información
Demostrar habilidades de trabajo en grupo en temas específicos y multidisciplinares
Demostrar habilidades de comunicación de resultados y redacción de informes técnicos
Distribuciones estadísticas. Distribuciones de frecuencias. Distribuciones bidimensionales. Regresión y correlación. Números índices y tasas de variación. Series temporales. Probabilidad.
Topic 1 Frequency distributions of one variable
The statistical data analysis.
Frequency distribution table
Graphic representation
Topic 2 Characteristics of a frequency distribution
Central and non-central trend measures
Dispersion measures
Shape measures
Concentration measures. Gini's Index
Topic 3 Two-dimensional frequency distributions
Two-dimensional frequency distribution tables.
Conditional and marginal distributions
Covariance and statistical independence
Topic 4 Regression and correlation
Linear Regression. The OLS method
Non-linear regression. Parabolic, Hyperbolic and exponential models.
The coefficient of determination. The coefficient of linear correlation
Forecasting
Topic 5 Index numbers
Definition, types and properties
Compounded index numbers. The Laspeyres' index' and the Paasche's Index
Repercussion and participation of a good in the index variation
Linkage of series. Deflation
Topic 6 Time Series
Definition and components
Trend and seasonality. The moving averages and the seasonal variation indexes.
Forecasting
Topic 7 Introduction to Probability
Operations with events. Basic set theory.
Definitions of probability. Kolmogorov's axiomatic definition.
Multiplication rule.
Total probability Theorem.
Bayes' Theorem
Practice
1. Construction of distributions of frequency and their graphical representation on a spreadsheet. Solving problems. 2. Calculation of the main descriptive measurements using a spreadsheet. Solving related problems. 3. Construction of index numbers (simple and complex), rates of change, impact and involvement using a spreadsheet. Solving related problems. 4. Construction of two-dimensional distributions and calculation of covariance using a spreadsheet. Regression analysis. Solving related problems. 5. Descriptive analysis of time series. Calculation of trend and seasonal variation rates using a spreadsheet. Solving related problems. 6. Solving problems related to the calculation of probabilities.
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.
Class in conventional classroom: theory, problems, case studies, seminars, etc
Explanation of the main theoretical statistical concepts that appears in each unit.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
Competences: CE04;CB3
Solving the problem sheets that corresponds to each unit through out the academic course.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to make decisions based on the analysis of the information.
- Ability to work in group, both on specific issues of the subject and on multidisciplinary issues.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
71.5
100
Class in laboratory: practical classes / internships
It has not been schedule this activity for the current year.
0
100
Class in the field or open classroom (technical visits, lectures, etc.). In general, activities that require special resources or planning
It has not been schedule this activity for the current year.
It has not been schedule this activity for the current year.
0
100
Class in a computer classroom: practical classes / internships
It has not been schedule this activity for the current year.
0
100
Assessment activities (continuous assessment system)
Exams and questionnaires to be solve by the students throughout the academic year.
Presentation of a quantitative report on real data provided by the professor.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2, CT4, CE04
3.5
100
Assessment activities (final assessment system)
Final exam to evaluate the knowledge acquired by the student during the course.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2, CT4, CE04
2.5
100
Tutorials
Advise students on the development of the Report that they have to hand in at the end of the course (20% of the final grade).
Answering questions that may arise after theoretical or practical classes to students.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to communicate the results and to make a descriptive and quantitative reports.
10
50
Student work: study or individual or group work
Development and writing of the final report corresponding to a statistical analysis of a data base.
Solving problems proposed by the professor.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to work in group, both on specific issues of the subject and on multidisciplinary issues.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Autonomous study of the concepts given in the Theory classes. Solve proposed problem sheets.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
100
0
Spoken or written exams
There will be one partial exam per semester.
The partial exam of the first semester will be valued with a 40% of the final grade of the course.
The partial exam of the second semester will be valued with a 40% of the final grade of the course.
The partial exam will consist in two parts each nof them valued with 20% of the final grade of the course. To pass the exam the student has to obtain a minimum of 3 points over ten in each part.
Those students who did not pass the course with the Continuous Evaluation system have the opportunity to pass the course in the Final Exam that will take place in the dates and classrooms designated by the Faculty in the official calls (June/July). This Final Exam will be valued with 80% of the final grade of the course.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
80 %
Participation and involvement in the teaching-learning process
Attend all classes and participation (making questions and proposals) related with the contents of the units.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
5 %
Evaluation of assignments and reports on practical sessions (final product, follow-up and contribution in the case of group work)
Final report concerning the statistical analysis of a data base.
The report has to be given in by the student in the form and date that the professor will state in a task in the virtual classroom or a similar method.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to work in group, both on specific issues of the subject and on multidisciplinary issues.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
15 %
Presentation and defence of assignments
Presentation of the final report to the rest of the students
0 %
Spoken or written exams
Final Exam will be taken at the end of the second semester and will take place in the dates and classrooms designated by the Faculty in the official call of June/July. The Final Exam will be valued with a 80% of the final grade of the course. It will consist in two parts, one theoretical and the other one practical (problems). The first partial exams will be valued with 45% and the second partial will be valued with 35%, summing both partial exams the total of 80% of the final grade of the subject. The content of final exam will correspond with the content of the first and second partial exams of the continuous evaluation system respectively.
In the case of multiple-choice exams, they may include a penalty for incorrect answers equal to or greater than the probability of randomly guessing that answer.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
80 %
Evaluation of assignments and reports on practical sessions (final product, follow-up and contribution in the case of group work)
Final report concerning the statistical analysis of a data base. Will be valued with a 20% of the final grade. The final report will contain a summary of the main topics of the course that will be valued with a 5% of the final grade of the course. This part correspond with the 5% PI of the continuous evaluation system.
Assessed learning outcomes:
- Knowledge of the different basic techniques to perform a descriptive data analysis.
- Ability to collect, organize and analyze data from a descriptive point of view.
- Ability to make decisions based on the analysis of the information.
- Ability to work in group, both on specific issues of the subject and on multidisciplinary issues.
- Ability to communicate the results and to make a descriptive and quantitative reports.
Competences: CG2; CT4; CE04;CB3
20 %
Author: Martín Pliego
Title: Introducción a la estadistica económica y empresarial (teoría y práctica)
Editorial: AC
Publication Date:
ISBN: 9788472881389
Author: Casas Sánchez
Title: Introducción a la estadística para administración y dirección de empresas
Editorial: Ramón Areces
Publication Date:
ISBN: 9788480045223
Author: Newbold, P
Title: Estadística para administración y economía
Editorial: Pearson
Publication Date:
ISBN: 9788415552208