Teaching guide for the course: BUSINESS STATISTICS II

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1 Teaching guide for the course: BUSINESS STATISTICS II Degree program: Degree in Business Administration and Management Year

2 Teaching Guide 1. Information about the course Name Subject Module Business Statistics II Statistics Quantitative Methods and Computing Code Degree awarded Study plan 2010 School Type Academic term Language Degree in Business Administration and Management School of Business Mandatory Second semester Spanish Academic year Second ECTS 4.5 Hours / ECTS 25 Total workload (hours) 112,5 Hours for theoretical classes Schedule for practical classes FCCE Timetable Classroom 2º Classroom FCCE Timetable Location 2º Classroom 2. Information about the instructor Instructor Manuel Ruiz Marín Department Quantitative and Computers Methods Area of knowledge Quantitative Methods Office location 3rd floor Tel: Fax: URL / WEB Office hours / Tutorials Location during tutorials 3rd floor - 1 -

3 - 2 -

4 3. Description of the course 3.1. Presentation: The course of Business Statistics II, to provide the students with advanced tools for analyzing economic data with practical application in different economic and business areas to help decision making in it. This course will determine a positive differentiation among future graduates and other traditional management technicians Location on the study plan The course Business Statistics II is an semi-annual course that is offered during the second year of the degree program in business administration and management Description of the course. Adaptation to the professional profile Business Statistics II is a highly practical course which teaches basic techniques for analyzing processes randomness. The student should be able to finish the course statistically test basic hypothesis about a population mean and proportions How it relates to other courses Prerequisites and recommendations It is essential to know the concepts studied in Business Statistics II. In addition, adequate monitoring of the matter requires, unlike other subjects, the existence of basic knowledge in the mathematical discipline that logically should have been acquired by the students earlier in their education. Thus, students should handle habitual agility mathematical notation. Likewise, the student must have knowledge of solving systems of equations, and integral calculus. Therefore it is recommended to continue to use the subject of Mathematics I and Mathematics leveling seminars given by the Department of Quantitative Methods Students with special needs Any student who has particular circumstances and may require special resources should let the professor know at the beginning of the quarter.. Skills - 3 -

5 4.1. Specific skills to be gained through the course - Ability to describe the information available - Predict future trends and behaviors - Ability to interpret cause-effect diagrams - Ability to consider an application of descriptive analysis of data for solving specific problems. - Ability to select sample size - Ability to test hypotheses 4.2. General / Transversal Skills INSTRUMENTAL SKILLS G01 Ability to analyze and summarize G02 Ability to organize and plan G03 Oral and written communication in the native language G04 Oral and written communication in a foreign language G05 Knowledge of computer programs and skills related to the field of study G06 Ability to search for and analyze information from different sources G07 Ability to solve problems G08 Ability to make decisions PERSONAL SKILLS G09 Ability to work as a team G10 Ability to work in an interdisciplinary team G11 Ability to work in an international context G12 Developing skills in personal relationships G13 Ability to work in diverse and multicultural environments G14 Ability to critique and self-critique G15 Ethical commitment at work G16 Work in stressful environments SYSTEMIC SKILLS G17 Auto-didactic skills G18 Ability to adapt to new situations G19 Creativity G20 Leadership G21 Initiative and entrepreneurial spirit G22 Quality driven G23 Sensitivity towards environmental and social issues SKILLS FOR APPLICABILITY G24 Ability to put the knowledge into practice G25 Ability to search for information and do research G26 Design and management of projects G27 Ability to communicate economic issues 4.3. Specific skills related to the degree E01 Ability to manage and run a small company or organization, understanding its competitive and institutional positioning and identifying its strengths and weaknesses - 4 -

6 E02 Ability to integrate in any functional area of a medium-sized or large company or organization, and smoothly carry out any management task entrusted E03 Ability to evaluate the situation and the foreseeable evolution of the company based on the relevant records of information E04 Ability to issue consulting reports on specific situations of companies and markets E05 Ability to write up projects for the overall management or for the functional areas of the company E06 Ability to identify the sources of relevant economic information and its content in order to analyze and know the relevant economic environment for the company E07 Ability to understand the economic institutions as a result and to apply theoretical or formal representations of how the economy functions E08 Ability to derive relevant information from the data which is impossible for non-professionals to know E09 Ability to regularly use information and communications technology in all professional tasks and activities E10 Ability to read and communicate in more than one language, especially in English E11 Ability to apply professional criteria based on the handling of technical instruments when analyzing problems E12 Ability to communicate fluently in their environment and work in a team 4.4. Results expected from the learning 1) Knowledge of different basic techniques of statistical inference. 2) Ability to collect, organize and analyze data from a descriptive point of view. 3) Ability to make decisions based on an analysis of the information. 4) Ability to work in a group, both on specific issues of the subject as well as on multidisciplinary issues. 5) Ability to communicate the results and to draw up descriptive and quantitative types of technical reports. 5. Content 5.1. Content according to the study plan Models of random variables. Probability distributions of the main statistics and their properties. Parametric estimation methods, both on time as per interval, and hypothesis testing Theory: modules and didactic units Topic 1: Random Variables Concept of random variable. Formal definition. Notations 1.2. Distribution functions of a random variable Properties

7 1.3. Discrete random variables Function of probability: Definition. F. Relationship 1.4. Continuous random variables Density Function: Definition. Characterization. F. Relationship 1.2. Expected value of a random variable Discrete and continuous case Properties expectation Models of Random Variables Bernoulli distribution The Binomial distribution The normal distribution of parameters μ, σ Some distributions related to Normal. Topic 2: Introduction to Statistical Inference: Sampling Theory Series of random variables and convergence The Central Limit Theorem Population. Sample. Types of Sampling Some important statistics Moments of the mean and sample variance Expectation and variance of the sample mean Expectation and variance of the sample variance Sampling in normal populations. Sampling distributions Distribution of the sample mean. With known variance Distribution of the sample variance Distribution of the sample mean. With unknown variance Distribution of the mean difference Variance ratio distribution Sampling distribution of a proportion. Topic 3: Estimation The problem: The point estimation The estimator of minimum mean square error Properties of estimators: unbiasedness and efficiency. Topic 4: Confidence Interval An introduction to confidence intervals A method for finding confidence intervals: The pivot method Confidence intervals in normal populations Confidence interval for the mean of a normal population Confidence interval for the variance of a normal population Confidence interval for mean difference. Topic 5: Test of statistical hypotheses Introduction Fundaments of hypothesis tests Hypothesis test in normal populations Test of hypotheses on the mean and variance Test hypotheses about a proportion

8 Test of hypotheses on the mean difference and variance ratio Test of difference of proportions hypothesis Program of practical application 1. - Simulation of discrete random variables and continuous type on a computer. Solving problems Empirical Central Limit Theorem. Simulation exercises. Solving problems 3. - Using specialized software for the construction of confidence intervals. Solving problems Using specialized software for parametric hypothesis testing. Solving problems Program summarized in English (optional) 5.5. Detailed planning of the teaching units (optional) - 7 -

9 6. Teaching methodology 6.1. Training activities 6.1. Training activities ACTIVITY Work of the professor Work of the student ECTS Theory class Presentation type of class taught using the lecture method. On-campus: Taking notes, asking questions 1 Answering questions raised by the students. Off-campus: Study of the subject 0.5 Problems are raised and solved, On-campus: Active participation, problem and class participation by the solving, asking questions Solving problems students is strengthened 1 through group and cooperative Off-campus: Study of the subject, solving of learning. problems raised by the professor 1 Collaborative and group project Practical application of computer programs Motivation and guidance of a project to be completed in a group. Guiding the students to understand how to prepare quantitative reports and present them publicly. Learning to use the basic tools of general software (spreadsheets) as well as specific software (SPSS) for descriptive analysis of data. Off-campus: Presentation and exhibition of the project consisting of a descriptive analysis of data obtained from a public database or collected by conducting a survey. On-campus: Active participation and learning to use the software Off-campus: Practice using the software by solving practical cases Tutorials Answering any questions about theory, solving problems and group project. On-campus: Asking of questions during the tutorial hours. Off-campus: Asking questions by 0.1 Exams Written evaluation (official exam), and grading of the content and presentation of the group project. On-campus: Attendance at formal review and presentation of the group project

10 7. Evaluation 7.1. Evaluation techniques Instruments Completion / criteria Weight Written tests Theoretical and practical questions representing 25% of the evaluation and 3-4 practical problems representing 75% of the evaluation. Up to 75% General skills (4.2) evaluated G01, G02, G07, G08 Results (4.4) evaluated Class attendance Personalized monitoring Up to 5% G14, G Group project* Evaluates skills Up to 20% G06, G09, G10, G17, G22, G24, 1,4,5 G25, G26. * The group project will be guided and overseen by the professor, who will give instructions beforehand regarding when and how the projects are to be presented. The professor will also set out certain minimum requirements that the group projects must also meet. A student who does not want to be evaluating by continuous systems will pass a final exam on all the material that will be the date of the final exam for the course. The student will have no other option to get partial exams in the course. 1,2, Mechanisms for control and tracking progress Class attendance: The student will be evaluated on classroom attendance during the course. Attendance will account for 5% of the final grade for the course (provided the student earns at least a 3.5 on the test). Since the class size is small, each student's learning is monitored almost personally. The student's participation in the theoretical and practical classes will be evaluated. Exam: an examination will be given on the contents covered during the course, which will include theoretical and practical questions and problems to be solved. The characteristics of the exam, as well as the date, time and location will be indicated on the announcement, which is given at least 15 days before the scheduled exam. It will require a minimum of 3.5 in order to make average in partial test. Group project: Students who turn in and present the group project may earn a maximum of 20% of the final grade for the course depending on the quality of the work, clarity and quality of the presentation, and if done in a foreign language (preferably in English). The tests (exams, classroom participation, solving practical cases, etc) enable detecting possible gaps and make it possible to consolidate the most important concepts of the course

11 Theory classes Class exercises Projects and reports Test on theory Problem solving Class attendance Group project Formative evaluation 7.3. Expected results / learning activities / assessment of results (optional) Results expected from the learning (4.4) 1. Knowledge of the different basic techniques for performing a descriptive analysis of data x x x x x x x x 2. Ability to collect, organize and analyze data from a descriptive point of view x x x x 3. Ability to make decisions based on analyzing the information x x x x x 4. Ability to work in a group, both on specific issues of the subject as well as on multidisciplinary issues 5. Ability to communicate the results and to draw up descriptive and quantitative types of technical reports x x x x x x x x x - 0 -

12 8. Distribution of the student s workload Second Semester 1 Teaching guide for the course "Business Statistics II"

13 2 Teaching guide for the course "Business Statistics II"

14 Clases teoría Clases problemas Laboratorio Aula informática TOTAL CONVENCIONALES Trabajo cooperativo Tutorías Seminarios Visitas Evaluación formativa Evaluación Exposición de trabajos TOTAL NO CONVENCIONALES Estudio Trabajos / informes individuales Trabajos / informes en grupo Convencionales ACTIVIDADES PRESENCIALES No convencionales ACTIVID PRESE Semana Temas o actividades (visita, examen parcial, etc.) 1 Repaso Repaso Tema Tema Tema Tema Tema Tema ,5 9 Tema Tema Tema Tema Tema Tema Repaso Periodo de exámenes Otros TOTAL HORAS Teaching guide for the course "Business Statistics II"

15 9. Resources and bibliography 9.1. Basic References Arnaiz Vellando, g., (1986), Introducción a la Estadística Teórica, Lex Nova. Durá Peiró: "Fundamentos de Estadística" Ed: Ariel Escuder Vallés R.: "Métodos Estadísticos Aplicados A La Economía" Ed. Ariel Economía. Fernández Abascal, Guijarro Rojo: "Ejercicios de Cálculo de Probabilidades" Ed: Ariel. Fernández Abascal: "Cálculo de Probabilidades y Estadística" Ed: Ariel. Gutiérrez Jaímez R. y otros.: "Curso Básico de Probabilidad" Ed: Pirámide. Llopis Perez J. "La estadística: una orquesta hecha instrumento" Ed: Ariel Ciencia. Martin Guzman, M.P. Y Martin Pliego, F. J., (1985), Curso Básico de Estadística Económica, Madrid: A.C. Martin Pliego, F.J. Y Ruiz-Maya Pérez, L., (1999), Fundamentos de Probabilidad, Madrid: A.C. Martin Pliego, F.J., Montero Lorenzo, J.Mª. Y Ruiz-Maya Pérez, L., (1998), Problemas de Probabilidad, Madrid: A.C. Martín Pliego, Ruiz Maya: "Estadística: I Probabilidad. II Inferencia Estadística" Ed: AC. Martín-Guzmán M.P. Martín Pliego F.J.: "Curso Practico De Estadística Económica" Ed. Ac Novales, A., (1996), Estadística y Econometría, Madrid: McGraw-Hill. Pérez Suárez, R. Y López, A.J., (1997), Análisis de datos económicos II. Métodos Inferenciales, Pirámide. Rohatgi, VK, 1976, An introduction to Probability Theory and Mathematical Statistic. John Wiley and Sons Uriel E. Muñiz M. "Estadística Económica Y Empresarial" Ed. Ac Uriel, E. Y otros: Econometría. El modelo lineal Ed: AC 9.2. Complementary References Barbancho, A.G.: "Estadística Teórica Básica. Probabilidad y Modelos Probabilísticos" Ed: Ariel. Escuder, R. "Introducción a la Teoría de la Probabilidad" Ed: tirant to blanch economía. Ruiz-Maya Pérez, L. y Martin Pliego, F.J., (1999), Fundamentos de Inferencia Estadística, Madrid: A.C. Sarabia Alegría J.M. : "Curso Práctico de Estadística" Ed: Cívitas. Martin Pliego, F.J., Montero Lorenzo, J.Mª. Y Ruiz-Maya Pérez, L., (2000), Problemas de Inferencia Estadística, Madrid: A.C. Kalbfleisch, J.G., (1984), Probabilidad e Inferencia Estadística I, Madrid:A.C. Murgui, J.S. "Estadística para la Economía y Administración de Empresas" Ed: Purchades. Tussel F. Garín A: "Problemas de Probabilidad e Inferencia Estadística" Ed:Tebar Flores. Lopez Cachero, M., (1985), Fundamentos y Métodos de Estadística Económica, Pirámide. Lopez De La Manzanara, J., (1977), Problemas de Estadística, Pirámide. Palacios Sánchez M.A., López Hernández F.A.: "Introducción a la Estadística para la Empresa" Horacio Escarabajal Editores. 4 Teaching guide for the course "Business Statistics II"

16 9.3. Online resources and other resources (Campus Virtual de la Universidad Rey Juan Carlos) (Centro de Investigaciones Sociológicas) (Instituto Nacional de Estadística) (Sociedad Internacional de los Profesionales de la Investigación en Encuestas) (Estadísticas en Europa) 5 Teaching guide for the course "Business Statistics II"

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