# 00914 - Statistics

### Course Unit Page

• Teacher Massimo Ventrucci

• Credits 8

• SSD SECS-S/01

• Language Italian

• Campus of Rimini

• Degree Programme First cycle degree programme (L) in Economics of Tourism (cod. 8847)

• Course Timetable from Feb 16, 2023 to May 25, 2023

### SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

## Learning outcomes

At the end of the course the students know fundamental concepts of statistics useful for the investigation of complex phenomena related to turism. In particular, students - are able to apply descriptive tools for data analysis; - are aware of the basic concepts of probability; - know the fundamental of statistical inference, hence can compute relevant summaries from the data and quantify the associated uncertainty. Pre-knowledge of mathematics is required.

## Course contents

part 1) DESCRIPTIVE STATISTICS

Basics of statistics and sampling; empirical distributions and their graphical representation; relevant summaries of a distribution; tools to examine association between two variables; linear regression

part 2) PROBABILITY AND STATISTICAL INFERENCE

Random events and sample space. Axioms of probability. Conditional probability. Density and probability fuctions of a random variable; expectaed value and variance of a random variable. Bernoulli and Binomial distributions. Normal and Normal Standard distribution. Central limit theorem. Sample variability of an estimator; the sample mean estimator and its properties, point estimation and confidence intervals; statistical tests; inference on the parameters of the simple linear regression model.

A. Agresti (A cura di A. Petrucci, M. Porcu). Metodi statistici di base e avanzati. Quinta edizione. Pearson.

S. Borra e A. Di Ciaccio (2014) Statistica. Metodologie per le Scienze Economiche e Sociali (III ed.), McGraw-Hill.

## Teaching methods

Frontal lectures based on slides and notes at the board. Lectures will be on methods and practicals (tutorials sessions with excersises on blackboard)

## Assessment methods

The exam will focus on:

- students' understanding of the basic statistics to produce empirical summaries and investigate relationships between two or more variables;

- students' understanding of the output of a statistical analysis.

EXAM STRUCTURE. The exam consists of two partial exams, each one consisting of a computer-based quiz administrated in a university lab, with both multiple choice questions and questions where it is required a numerical input. More details will be given during the course. To pass the whole exam students have to pass each single partial exam.

Students taking the exam are required to register first, following the procedure in almaesami webpage. During the exam, students are allowed to use their hand-written personal notes, a copy of the table of the standard Normal cumulative distribution and the table of the T-student (both can be found in the textbook). It is forbidden to use any extra material that is not hand-written personal notes like books, tablet, smartphone during the exam.

REGISTRATION. Grades are normally published a couple of days after the exam date on almaesami. The teacher will register the grades on the office hours date right after the exam; in the same office hours students can ask an appointment to discuss with the teacher the mistakes they have done in the exam.

REJECTING THE GRADE. Students can reject the grade obtained at the exam once. To this end, he/she must email a request to the instructor within the date set for registration. The instructor will confirm reception of the request within the same date. Rejection is intended with respect to the whole exam, whose grade is the average of the grades obtained in the two mid-terms. If the grade is rejected, the student must retake the full exam (consisting of both parts). The only grade that can be rejected without any communication from the student is the one of the first mid-term.

Students sitting the first mid-term can take the second mid-term on the first examination date set for the full exam, right at the end of the integrated course. A student can sit the second mid-term only once; if he/she fails or rejects the grade obtained, he/she will have to resit the full exam and will lose the grade obtained in the first mid-term.

## Teaching tools

Slides and blackboard (or an ipad for notes taking).

## Office hours

See the website of Massimo Ventrucci