Teaching guide for the course: BUSINESS STATISTICS I Degree program: Degree in Business Administration and Management Year 2012-2013 - 0 -
Teaching Guide 1. Information about the course Name Subject Module Business Statistics I Statistics Quantitative Methods and Computing Code 510101004 Degree awarded Study plan 2010 School Type Academic term Language Degree in Business Administration and Management School of Business Mandatory Annual Spanish Academic year ECTS 7.5 Hours / ECTS 25 Total workload (hours) 187,5 Hours for theoretical classes Schedule for practical classes First FCCEE Timetable Classroom 1º Classroom FCEE Timetable Location 1º Classroom - 1 -
2. Information about the instructor Instructor Department Area of knowledge Office location Tel: E-mail: URL / WEB Manuel Ruiz Marín Practical lectures: Roberto J. Cañavate Bernal Quantitative and Computer Methods Quantitative Methods 3 rd floor Office hours / Tutorials M. Ruiz: 968325901 R. Cañavate: 968325783 manuel.ruiz@upct.es r.canavate@upct.es http://metodos.upct.es Location during tutorials Office 3.19 Fax: 968325745 Tuesday and Thursday from 8 am to 10 am, and from 3:30 pm to 4:30 pm - 2 -
3. Description of the course 3.1. Presentation: The course Business Statistics I aims to provide the student with tools for analyzing economic type data with a very practical application in different areas of a firm, facilitating the decisionmaking process therein. This course will mark a positive distinction between future college graduates and other traditional business administrators. 3.2. Location on the study plan The course Business Statistics I is an annual course that is offered during the first year of the degree program in business administration and management. 3.3. Description of the course. Adaptation to the professional profile Business Statistics I is a very practical course which teaches the technical principles of descriptive analysis at an introductory level. Thus, at the end of the course, the student must be able to establish adequate measurements for the economic variables, relate such variables, determine their evolution, carefully weigh data, adequately represent the data and make predictions about the evolution of certain magnitudes. 3.4. How it relates to other courses Prerequisites and recommendations Unlike other courses, in order to adequately follow the subject matter of this course, someprevious knowledge of math is required, which the student should have likely acquired during the previous stages of his/her education. Thus, the student should be at ease with performing elementary mathematical operations +, -, x,, elementary powers, using parentheses, brackets, etc., as well as usual mathematical notation. The student should also know how to solve systems of equations and matrix calculations. For these reasons, it is recommended that the student successfully pass the course Mathematics I and the leveling seminars in Mathematics proposed by the Department of Quantitative Methods. 3.5. 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. - 3 -
4. Skills 4.1. Specific skills to be gained through the course - Ability to look for knowledge that is new and able to provide an innovative approach to decision making - 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. 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 -
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 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 the different basic techniques for performing a descriptive analysis of data 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 -
5. Content 5.1. Content according to the study plan Basic concepts of the mathematics of numbers, including addition and multiplication symbols Construction of a distribution of frequencies of one-dimensional variables and calculation of characteristics of such distribution Construction of different index numbers (simple and complex) and calculation of rates of change in impact and participation Twodimensional frequency distributions, marginal and conditional distributions Calculation of the times with respect to the origin and the average Calculation and meaning of covariance and its matrix expression Descriptive analysis of time series Introduction to the theory of probability 5.2. Theory: modules and didactic units Topic 1: Statistical distributions of a character 1.1. Descriptive statistics and statistical inference (**) 1.2. Applications of Statistics in the Company 1.3. Definitions 1.3.1. Population and Sample Census and Survey 1.3.2. Discreet and continuous statistical variables Quantitative and qualitative variables 1.4. Distribution of frequencies: Grouped and non-grouped into intervals (**) 1.5. Graphic representations Topic 2: Characteristics of a distribution of frequencies 2.1. Characteristics of a distribution of frequencies 2.2. Central measurements of position 2.2.1. The arithmetic, geometric and harmonic mean Properties 2.2.2. The median and the mode 2.3. Non-centered measurement of position: Quartiles, deciles and percentiles 2.4. Absolute measurements of dispersion: Interquartile range, mean deviation, variance Standard deviation Properties 2.6. Relative measurements of dispersion 2.6.1. Openness coefficient, Relative range, Semi-interquartile range 2.6.2. Pearson's Coefficient of Variation Index of dispersion with respect to the median 2.7. Measures of concentration: Gini Index and Lorenz Curve Topic 3: Index numbers and Rates of change 3.1. Concept and applications 3.2. Simple index number Rates of change 3.3. Complex index numbers 3.4. Types of index numbers: Price, Production and Value 3.5. Change of base period Renovation and joint 3.6. Deflation of economic series 3.7. Participation and impact of a product on a general index (*) 3.8. The CPI and other indexes developed in Spain Topic 4: Two-dimensional distributions 4.1. General concepts - 6 -
4.2. Two-dimensional distributions of frequencies: Tables of correlation and contingency 4.2.1. Marginal and conditional distributions 4.3. Moments in two-dimensional distributions: Moments with respect to the origin and the average 4.4. Covariance 4.4. Statistical independence Topic 5: Regression and correlation 5.1. Concept of linear fit 5.2. The method of least squares and normal equations 5.3. Least squares fit to a straight line Properties of the regression line 5.4. Coefficient of determination and correlation 5.4.1. Residual variance 5.4.2. Relationship between the variances Sy2; Sy*2; Se2 5.4.2. The coefficient of determination 5.4.3. The linear correlation coefficient 5.5. Non-linear regression and correlation 5.6. Nonlinear adjustments: Hyperbolic, potential, exponential, and parabolic adjustment 5.7. Multiple linear regression 5.7.1. Adjustment to a least-squares hyperplane 5.7.2. The coefficient of multiple determination 5.8. Prediction Topic 6: Classic time series analysis 6.1. Introduction: Numeric description and graphic representation 6.2. Components of a time series 6.3. Types of diagrams: Determining the type of diagram 6.4. Analysis of the trend 6.4.2. Method of moving averages 6.4.4. Method of adjusting to a function 6.5. Analysis of seasonality 6.5.1. Ratio (or difference)-to-moving average method 6.5.2. Method of the relationships of the monthly averages with respect to the trend 6.6. Prediction TOPIC 7: Probability 7.1. Introduction Stochastic phenomena Random experiment 7.2. Sample spaces Events 7.3. Axiomatic definition of probability 7.3.1. Kolmogorov's Axioms 7.3.2. Consequences of the axioms 7.4. Conditional probability 7.4.2. The theorem of total probability 7.4.3. Bayes' theorem 7.5. Independence of events - 7 -
5.3. Program of practical application 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. 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. 5.4. Program summarized in English (optional) 5.5. Detailed planning of the teaching units (optional) - 8 -
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 2 Answering questions raised by the students. Off-campus: Study of the subject 1.5 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. 0.5 1 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 e-mail 0.3 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. 0.2 7.5-9 -
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, G15 3.5 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. 1,2,5 7.2. 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. - 10 -
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 -
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 TOTAL NO PRESENCIALES ENTREGABLES 8. Distribution of the student s workload FIRST QUARTER Convencionales ACTIVIDADES PRESENCIALES No convencionales ACTIVIDADES NO PRESENCIALES Semana Temas o actividades (visita, examen parcial, etc.) 1 Presentación, Tema 1 3 3 3 2 Tema 1 1 1 1 3 1 1 2 5 3 Tema 2 2 1 3 1 1 2 5 4 Tema 2 2 1 3 1 1 2 1 3 7 5 Tema 2 1 2 3 2 1 1 4 7 6 Tema 2 2 1 3 1 1 2 1 1 4 8 7 Tema 2 1 2 3 4 4 2 1 1 4 11 8 Tema 3 2 1 3 1 1 2 2 1 1 4 9 9 Tema 3 2 1 3 1 1 2 1 1 4 8 10 Tema 3 2 1 3 1 1 2 2 1 1 4 9 11 Tema 3 2 1 3 2 2 2 1 1 4 9 12 Tema 3 2 1 3 1 1 2 2 1 1 4 9 13 Tema 4 2 1 3 1 1 2 1 1 4 8 14 Tema 4 1 1 1 3 1 1 2 1 1 4 8 15 Repaso primer parcial 1 2 3 1 2 1 1 4 Periodo de exámenes Otros TOTAL HORAS TOTAL HORAS 4 4 8 8 12 20 17 8 45 10 6 2 4 21 34 14 11 59 118 1
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 TOTAL NO PRESENCIALES ENTREGABLES SECOND QUARTER Convencionales ACTIVIDADES PRESENCIALES No convencionales ACTIVIDADES NO PRESENCIALES Semana Temas o actividades (visita, examen parcial, etc.) 1 Repaso 2 2 2 2 Repaso 2 2 1 1 3 3 Tema 5 2 2 1 1 3 4 Tema 5 2 2 1 1 2 1 1 5 5 Tema 5 1 1 2 1 1 1 2 3 6 6 Tema 5 1 1 2 1 1 2 1 1 2 6 7 Tema 5 2 2 1 1 1 2 3 6 8 Tema 5 1 1 2 2 1 3 1 1,5 2,5 7,5 9 Tema 6 2 2 2 2 4 1 2 3 9 10 Tema 6 1 1 2 1 4 5 1 2 3 10 11 Tema 6 1 1 2 2 2 4 12 Tema 6 1 1 2 1 1 2 2 5 13 Tema 6 1 1 2 2 2 4 14 Tema 6 1 1 2 1 1 2 2 5 15 Repaso 1 1 2 2 2 Periodo de exámenes Otros TOTAL HORAS TOTAL HORAS 4 4 6 6 10 17 8 5 30 8 6 2 4 4 24 25 11 35,5 85,5 2
9. Resources and bibliography 9.1. Basic bibliography José A. García, Fernando López, Mª Ángeles Palacios, Manuel Ruiz Marín. Introducción a la estadística para la Empresa, Horacio Escarabajal Editores. 2000. MARTIN GUZMAN, M.P; MARTIN PLIEGO, F.J. Curso básico de estadística económica. 3ª ED. Madrid: AC, 1991. MARTIN PLIEGO, F.J; RUIZ-MAYA PÉREZ, L. Fundamentos de probabilidad. Madrid: A.C., 2006. MARTIN PLIEGO, F.J; MNTERO LORENZO, J.Mª; RUIZ-MAYA PÉREZ, L. Problemas de probabilidad. 2ª ed. Madrid: Paraninfo, 2009. Newbold P. "Estadística para los Negocios y la Economía" Ed: Prentice Hall, 2000 9.2. Additional bibliography CASAS SÁNCHEZ, J. M., y otros: Ejercicios de estadística descriptiva y probabilidad para economía y administración de empresas, Pirámide, 2006. ERNESTO CASA ARUTA, 200 problemas de estadística descriptiva, Ed: Vicens- Vives, 1994. FERNÁNDEZ CUESTA, C; FUENTES GARCÍA, F. Curso de estadística descriptiva. Barcelona: Ariel, 1995. 524 p. ISBN 84-344-2104-6 9.3. Online resources and other resources http://ocw.bib.upct.es/ http://www.carm.es/econet/ www.ine.es http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/ http://www.lacaixa.comunicacions.com/se/index.php?idioma=esp 3
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