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Second Semester 
Teaching style
Lingua Insegnamento

Informazioni aggiuntive

Course Curriculum CFU Length(h)


The aim of the course is to provide students with the basics of statistics in order to get tools and methodologies useful for data analysis, probability calculus and statistical inference.
At the end of the course, the student will know the main indicators used for the descriptive data analysis, and assess the importance of the implementation of a statistical system within a company. Furthermore the student will be able to figure out what it means to carry out a sample and obtain estimates from statistical inference methods.
In keeping with the educational objectives of the degree course in Economics and Business Administration, the expected learning outcomes are also declinable according to all the Dublin Descriptors, following this scheme:

The course is based on the study of descriptive and inferential statistics to analyze data and make predictions in order to provide the necessary tools for data analysis activities carried out within companies.

The statistical models explained during the lectures will be applied in classroom during the exercises. The goal is to make students able to figure out the statistical tools and to know how to use them in their future professional activities.

During the lectures the students will be asked to make decisions to support the management of a company, applying statistical tools on real data.

Students will be encouraged to intervene in the classroom through the analysis of case studies for which they will have to indicate the most appropriate statistical methods to be used, what variables should be considered in the data analysis, what results have been obtained. Students will be able to support and motivate their opinions with the acquired knowledge of statistics.

The theoretical lectures and the supplementary activities will improve and enhance the learning ability of students also in the continuation of their academic and professional career.


It is recommended knowledge of the topics covered in the course of general mathematics and in particular operations with real numbers and their properties - summation and product symbols - systems of equations and inequalities of first and second degree - elementary function graphs - concept of limit, derivative and integral.


- Part I Descriptive Statistics
The survey statistics and its phases. Population and sample. Quantitative and qualitative statistical variables. Measurement scales. Frequency distribution and graphical representations of a variable. Position and variability indices. Shape of a distribution. Joint study of two variables: charts of double variables, contingency table, conditional and marginal frequencies. Independence and relationship indices, in particular the linear correlation coefficient. Linear regression.

- Part II Probability.
Events and logical operations on events. Interpretations of probability. Basic theorems of probability of the union and intersection of events. Conditional probability, independent events, Bayes's theorem. Discrete and continuous random numbers: probability mass function and probability density function. Expected value and variance of a random number. Chebyshev's inequality. Function of a random number, expected value and variance for a linear function. Random distributions: Bernoulli, Binomial, Poisson; Normal and Uniform. Random vectors: joint probability distribution, independence; linear combinations. Sequences of random numbers and the central limit theorem.

- Part III Statistical inference.
Sampling, statistics and their sampling distributions. Distribution of the sample mean. The sample variance. Point estimation, properties of point estimators. Interval estimation, confidence intervals for large samples. Statistical tests: critical region, the first and the second type of error. The pvalue. Tests on mean, on the proportion and the difference of means and proportions (independent populations). Univariate and bivariate goodness of fit test (test of independence).

- Part IV Statistics applied on tourism
Istat, tourism indicators.

Teaching Methods

The course consists of 72 hours of lectures. In addition, there will be 40 hours of exercises, of two hours each, to test the knowledge acquired in class on the understanding of descriptive statistics, the probability and statistical inference.

Verification of learning

The learning level will be verified through a report, in which students will be asked to determine which methods of analysis is correct to apply, to solve problems of statistical inference and, finally, to comment the results. The correct performance of the examination requires that the student is capable of analyzing the statistical variables, choosing the correct indicators for the analysis, performing methodologies and analyze the results.
According with the descriptors identified in the aims, it will be evaluated:
1) clarity in expressing the theoretical contents of descriptive and inferential statistics.
2) the ability to re-elaborate the concepts and apply them (evaluation of ability to apply knowledge and understanding).
3) the ability to choose which statistical methodology is correct and what indicators are more appropriate to use, explaining the reasons of the choice, and evaluating the results obtained (evaluation of independent judgment).
4) the expositive clarity, the capacity for analysis and exposition of results (evaluation of communication skills).
5) the knowledge of descriptive and inferential statistics (evaluation of learning ability).
The score of the exam is out of thirty. At the end of the first part of the course there will be a mid-term examination. That proof is arranged at start in agreement with the other professors who teach in the same semester and in the same year that provide a mid-term examination, to ensure that there is no overlap and that students have sufficient time interval between different examinations. The test consists of exercises related to the first part of the course (from Descriptive Statistics to Probability, including linear regression). Half of the exercises involve Descriptive Statistics and half Probability. The final grade is out of thirty and is indicative of the level of global preparedness. It is set up an evaluation system that overcomes one of the parties (Descriptive or Probability), or both. If the student passes only one of the parties at the end of the course he will support a practice examination that provides for the recovery of the part not exceeded, as well as the second part of the course (Statistical Inference). Then it will follow a general oral exam to define the final vote. If the student in the intermediate test exceeds both sides with a low rating, then at the end of the course he will support only a practical test on the second part (Statistical Inference) and a oral exam. If the student exceeds the intermediate test both sides with a medium-high rating, then he gets the exemption of the second part (as a practice test) and he will make just a oral exam for the final definition of the vote.

The allocation range of the final grade is from 18/30 to 30/30. A student will get a close-to-18 grade if he shows an elementary knowledge level of the subject, or if he knows the descriptive and inferential statistics and has a minimum of analytical ability on the results analysis. Conversely a student will get a close to 30/30 evaluation, with possible praise, when it will be able to correctly identify the variables and the methodology to be applied, when it will also be able to figure out the inferential statistics and its implications.


Recommended book is
- Borra S, Di Ciaccio: Statistica. Metodologia per le scienze economiche e sociali, ultima ed. Mc Graw Hill.
- Newbold P Carlson WL Thorne B: Statistica (seconda edizione italiana), Pearson.

Other books
- Cicchitelli G, Probabilità e Statistica (ultima ed.), Pearson.
- Piccolo D: Statistica per le decisioni, ultima ed. Il Mulino, Bologna.

More Information

Tips to profitably attend classes.

Being a discipline with many practical implications and different operational implications, it is essential to approach the study of Statistics with critical approach, evaluating each time the reasons for the application of one or another method as well as connections, conceptual and operational, among the various topics.
It is recommended to attend the lectures because, as the teacher will highlight the connections among the various statistical tools explaining the advantages and disadvantages relating to their application, just in order to promote, thereby, a better understanding of the topics in the program as possible.
It is advisable also to participate actively in class taking notes and asking for further explanations immediately when a topic does not appear completely clear. The understanding of the topics must be immediate and full. Being different topics connected with each other is neither useful nor advisable to leave, even temporarily, some parts of the program.
Finally, it is important to study different topics from time to time, keeping the individual preparation in step with the explanations of the teacher.

Questionnaire and social

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