Academic year
2023/2024 Syllabus of previous years
Official course title
Course code
CT9004 (AF:451687 AR:245377)
On campus classes
ECTS credits
Degree level
Bachelor's Degree Programme
Educational sector code
2nd Term
Course year
Go to Moodle page
The course falls within the area of ICT technologies and statistical methods. Specifically, it covers the foundational notions of quantitative methods, with a focus on the statistical techniques for the analysis of company data and social media data.
The course belongs to the quantitative analysis subjects fo the Hospitality Innovation and e-Tourism degree and it allows the student to acquire knowledge and comprehension of the main tools for the analysis of data in the area of management and their use for decision making in situations of uncertainty in the area of tourism and hospitality.
The goal of the course is to provide the basic notions of probability and statistics and the ability to sue some of the data analysis softwares.
By the end of the course, the student will be able to select the methodologies that best fit the problem of interest, to analyse the related data, interpret and communicate the results of the analysis in order to drive the decision makers to the best strategy at hand.
1. Knowledge and comprehension:
- to know the basic tools for the graphical representation of the main characteristics of a dataset
- to know the basic notions of probability and inference
- to know the basic notions of statistics
2. Applying knowledge and understanding:
- to be able to use the proper software tools for data analysis and for the presentation of results
- to be able to use the proper terminology in the process of application and presentation of the acquired skills
3. Making judgements
- to be able to put the acquired skills into context, by identifying the best methods for the task of interest
4. Communication skills
- to be able to discuss with the teacher, by applying critical thinking with respectful manners
5. Learning Skills
- to be able to exploit and harmonize information from different sources such as books, notes, slides, video and practical sessions
- to be able to evaluate oneself by means of tests and exercises
No prerequisite is required, but the student must have some familiarity with elementary mathematical operations, simple equations and disequations, and logical skills.
The course provides a practical introduction to probability and statistics. The first part of the course has the goal of introducing the most used techniques for the graphical representation of data. Next, basic notions of probability and probability distributions are presented. The last part of the course covers inference methods for estimation, prediction, and hypothesis verification. Theoretical lessons are motivated by practical examples and applications to real-world industry-related problems. The Excel software is used for the analysis of data and for statistical inference. We introduce the student to the use of other statistical software such as JASP with a friendly graphical user interface.
Descriptive statistics: population and samples; random variables; graphical representations and indices for quantitative and qualitative variables; relationships between qualitative variables and Chi-square score; relationships between quantitative variables, correlation, and regression.
Inference: sample distributions; mean and variance estimation; confidence intervals; hypothesis verification and p-value.
John Buglear, Adrian Castell Stats Means Business – Statistics with Excel for Business, Hospitality and Tourism. Second edition, 2019, Third edition. Routledge, ISBN: 978-1-138-58822-6

Open source guide for JASP program
The assessment will be based on a final written exam. A project work can help for gaining up to 3 points for final exam. Details will be provided on moodle and during the course.
Lecture and practical sessions
written and oral
Definitive programme.
Last update of the programme: 18/07/2023