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B1934 - Statistics

Academic Year 2024/2025

                
                        Docente:
                        Silvia Bianconcini
                    
                        Credits:
                        10
                    
                        SSD:
                        SECS-S/01
                    
                        Language:
                        English
                    
                        Teaching Mode:
                        Traditional lectures
                        
                            Campus:
                            Forli
                        
                            Corso:
                            First cycle degree programme (L) in
                            International Studies (cod. 5949)

                            Teaching resources on Virtuale
                        
                                    Course Timetable
                                
from Sep 19, 2024 to Dec 12, 2024

Learning outcomes

The aim is to lead the student in learning the basic statistical notion. The first theoretical part introducing the basic statistics is followed by an application part with practical exercises.

Course contents

The course program is organized in three parts as described below.

Exploratory Data Analysis

The data matrix. Types of variables. Frequency tables. Graphical representations. Summary measures of position and dispersion. Association of two quantitative variables, covariance and correlation coefficient. Outline of simple linear regression.

Probability Theory

Random experiment, sample space and events, probability measure. Conditional probability, independence. Random variables. Expected value and variance of a random variable. Discrete and continuous random variables. Bernoulli and binomial distribution. Gaussian distribution.

Inferential Statistics

Random sampling. Parametric statistical models. Sampling distributions. Point estimation. Bias and mean squared error. Confidence intervals for the mean of a Gaussian population. The Student t distribution. Approximate confidence interval for a probability. Hypothesis testing on the mean of a Gaussian population. The p-value. Inference on a proportion.

Readings/Bibliography

Cicchitelli G., D'Urso P. and Minozzo M. (2021). Statistics: principle and methods. Pearson Edition.

Teaching methods

Teacher's lectures and tutorials.

Assessment methods

For attending students, there are 2 midterm tests during the Statistics course, otherwise, is possible to do only one full test in the ordinary examination session.

To pass the exam the student score has to be greater than or equal to 18 in the full examination and in midterm tests (for attending students) the average score has to be not less then 18.

If the student does not pass the examination in the following course session, he/she can give back it only in June session.

Teaching tools

Slides of the course, materials for self-assessment.

Office hours

See the website of Silvia Bianconcini

SDGs

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