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Applied Statistics

Code: 103746 ECTS Credits: 6
2024/2025
Degree Type Year
2502904 Hotel Management FB 1

Contact

Name:
Tatiana López Orozco
Email:
tatiana.lopez@uab.cat

Teachers

Juan David Vega Baquero

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

There are no prerequisites


Objectives and Contextualisation

At the end of the course, students will be able to:

  1. Identify what types of variables are appropriate for quantitative analysis in hospitality and tourism.
  2. Collect, analyze and represent quantitative and qualitative information in the hotel and tourism industries
  3. Consider the importance of collecting, analyzing and representing statistical data considering gender and sustainability perspectives in the sector.
  4. Analyze data, populations and samples, as well as the association between variables to assess the economic dimension of the sector.
  5. Interpret the results of statistics from a critical perspective, taking into account aspects of gender inequality and sustainability in the sector.
  6. Know the main concepts and parameters of descriptive statistics and establish criteria for presenting data at the analytical and graphical level.
  7. Identify variables related to hospitality and tourism characterized by randomness and analyze them using basic probabilistic techniques.
  8. Implement statistical inference using test and estimation hypotheses.
  9. Perform time series analysis and forecast key tourism variables.
  10. Establish the advantages and disadvantages of different statistical methods for a given type of observations.
  11. Identify key sources of quantitative data in the sector (for example: publications, surveys, databases, etc.) and know how to use them.

Competences

  • Adapt to changes in technology as they occur.
  • Analyse, diagnose and support and take decisions on the organisational structure in the hotel and catering sector.
  • Be able to self-evaluate knowledge acquired.
  • Demonstrate broad knowledge of the organisation and management of company operations, with emphasis on applied management models and the application of quantitative and qualitative techniques.
  • Develop a capacity for independent learning.
  • Manage and organise time.
  • Manage communication techniques at all levels.
  • Work in teams.

Learning Outcomes

  1. Adapt to changes in technology as they occur.
  2. Analyse and qualitative and interpret quantitative information regarding management models in the tourism sector.
  3. Analyse, data, populations and samples, tables and graphs, and the association between variables, to be able to valuate the economic dimension of tourism.
  4. Be able to self-evaluate knowledge acquired.
  5. Collect, present and analyse qualitative and quantitative information referring to the tourist sector.
  6. Develop a capacity for independent learning.
  7. Identify referential situations in the tourist sector characterised by randomness and analyse them using basic probability tools.
  8. Manage and organise time.
  9. Manage communication techniques at all levels.
  10. Work in teams.

Content

Topic 1: Preliminary Concepts

Basic concepts in statistics. Organization and presentation of data: tables and distribution of frequencies. Obtaining data through questionnaires and tabulation. Bar charts, histograms and other graphical representations.

Topic 2: Measures of central tendency

Concepts of mean, median, mode, and quintiles. Relationship between measures.

Topic 3: Dispersion and concentration measures

Range, interquartile range, variance, standard deviation, coefficient of variation, Lorenz curve and Gini coefficient, use of the Gini in tourism.

Topic 4: Measurements of form

Asymmetry and kurtosis measurements. Box plot.

Topic 5: Series of two variables

Definition and graphic representation. center tendency. Statistical dispersion. covariance

Topic 6: Statistical dependency

Correlation: concept, procedure and application. Pearson's correlation coefficient. Linear regression fit between two variables. Least squares approach.

Topic 7: Probability

Operations with probabilities. Assignment of probabilities: random variables and their distributions.

Topic 8: Time series

Definition and graphic representation. Time series components. Seasonal variation. Seasonal indices. Seasonal adjustment.


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Master Classes 50 2 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Type: Supervised      
Tutorships 45 1.8 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Type: Autonomous      
Practical works 25 1 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Study 22 0.88 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

Teaching languages
Spanish

The course has three teaching and learning methods:

  1. Theoretical sessions
    • During the classes, the concepts will be explained theoretically and exemplified with practical applications. Some sessions will require student participation to solve problems.
  2. practice sessions.
    • During these sessions, the topics covered in the theoretical sessions will be reviewed through exercises, group projects and individual tests that will be carried out throughout the course. Case studies related to tourism will be presented and variables specific to this industry will be analyzed.
    • Students will receive guidance from the teacher to carry out a project that involves the use of statistical and computer skills. Specialized software will be used as much as possible during the sessions.
  3. Self-learning
    • The Virtual Campus will be used as a complement and as an alternative means of communication between students and teachers. All relevant course material, examples and exercises will be attached online.
    • Each student must manage their time to study and solve the proposed problems, in addition to working on a research project using statistical data in the tourism sector that will be presented at the end of the course.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Midterm exam 1 20% 2 0.08 1, 2, 3, 4, 5, 6, 8, 9, 10
Midterm exam 2 20% 2 0.08 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Practical exercises - Individual and group 40% 0 0 1, 2, 3, 4, 5, 6, 7, 8, 9
Project and presentation 20% 4 0.16 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

Students can choose between continuous assessment or direct access to the final exam (a single final assessment).

A) CONTINUOUS ASSESSMENT

The continuous assessment system involves the periodic presentation of individual and group work and activities, in addition to the completion of two partial exams to consolidate the concepts and topics developed in class with a value for each of 20% of the grade. end of the subject. In order to average the results obtained in these two partial exams, the student must achieve a minimum score equal to or greater than 4 points in both exams.

The Virtual Campus will detail the delivery dates of the work and the completion of the two partial exams.

Students who do not pass the subject through continuous evaluation will be evaluated by the single evaluation system, not taking into account the grades obtained previously.

B) SINGLE EVALUATION: Final exam (all subject).

Date and time established, according to the academic calendar, in the Official Program of the Center.

There will be a single type of final exam, without differentiation between students who have passed the continuous assessment and those who have not.

C) RE-ASSESSMENT:

Day and time established, according to the academic calendar, to the Official Program of the Center.

Students who have obtained a grade equal to or greater than 3.5 and less than 5 in the final evaluation may take the re-evaluation.


Bibliography

Buglear, J. (2010). Stats means business- Statistics with Excel for business, hospitality & tourism (2nd ed.). New York: Elsevier.

Casas Sánchez, J., Martos Gálvez, E., & Tejera Martín, Í. (2011). Estadística aplicada al turismo. Editorial Centro de Estudios Ramón Areces.

Davis, G., & Pecar, B. (2009). Business Statistics using Excel (2nd ed.). Oxford University Press.

Good, P. I., & Hardin, J. W. (2012). Common errors in statistics (and how to avoid them). [Hoboken, N.J.]: John Wiley.

Newbold, P., Carlson, W. L., & Thorne, B. (2013). Statistics for business and economics. Harlow, Essex: Pearson Education.

Parra López, E. (2007). Estadística para turismo. McGraw-Hill España. Disponible en línea

Ross, S. M. (2010). Introductory statistics. Amsterdam: Elsevier: Academic Press.

Rugg, G. (2007). Using statistics: a gentle introduction. Maidenhead: McGraw-Hill.

UNWTO (2010) International Recommendations for Tourism Statistics 2008, Statistics and Tourism Satellite Account, World Tourism Organization, New York. Available online

World Tourism Organization (2020), Methodological Notes to the Tourism Statistics Database, 2020 Edition, UNWTO, Madrid, DOI: https://doi.org/10.18111/9789284421473. Available online

Yearbook of Tourism Statistics, Data 2014 – 2018, 2020 Edition. (2020). Available online


Software

Microsoft Office (Excel, Word, PowerPoint)


Language list

Name Group Language Semester Turn
(TE) Theory 1 Spanish second semester morning-mixed