BASIC STATISTICS

Course objectives

The main objective of the course is to make students able to carry out a quantitative analysis of real phenomena and to interpret the results. To this end, during the lessons the main tools and methods of descriptive and inferential (univariate and bivariate) statistics will be discussed, focusing on both the theoretical/methodological aspects and the analysis of real data. In particular, many examples based on real problems will be shown, especially concerning phenomena in the business, socioeconomic and financial fields. The student who is sufficient to the exam: 1) will have acquired the basic tools of statistics, such as descriptive statistics and basic inferential techniques; 2) will be able to apply all the methodologies described in the course to real data, choosing the most appropriate tools to be applied in the analysis of specific phenomena of interest; 3) will be able to interpret, discuss and criticize the obtained results. The development of this specific skill also derives from frequent discussions encouraged by the teacher, during the presentation of empirical applications; 4) will be able to communicate the methodologies as well as the results of empirical analysis with a proper language. This specific skill also derives from active participation to discussion in the classroom encouraged by the teacher; 5) will be able to to autonomously carry out statistical analyses and to understand more complex concepts and methodologies. In particular, these tools include tables and graphs, statistical indices, statistical relationships between phenomena, inferential procedures.

Channel 1
MARIA RITA SEBASTIANI Lecturers' profile

Program - Frequency - Exams

Course program
Basics of Statistics: key terms. Describing data sets: frequencies, tables and graphs. Summarising data sets: mean, median and q-quantiles, mode; variance, standard deviation and other statistical measures of variability and concentration; symmetry and statistical measures. Index numbers and price index. Bivariate distribution, statistical dependence and simple linear regression. Fundamentals of probability. Discrete random variables and normal random variable. Sample and population; distribution of sampling statistics. Point and interval estimation. Testing statistical hypotheses.
Prerequisites
Basic knowledge of mathematics
Books
Cicchitelli G., D’Urso P., Minozzo M. (2022). Statistica: principi e metodi. Quarta Edizione. Pearson editrice. Sebastiani M.R. (2022). Esercitazioni di Statistica. Quarta edizione. Esculapio Editrice. In alternative, students can use other academic handbooks of Statistics containing all the topics included into the exam programme.
Teaching mode
Classroom teaching
Frequency
Not compulsory but advisable
Exam mode
Written exams (exercises and theory questions). In addition, students can ask for supplementary oral examination in aim to complete evaluation of understanding of topics.
Bibliography
Cicchitelli G., D’Urso P., Minozzo M. (2017). Statistica: principi e metodi. Terza Edizione. Pearson edizioni. Sebastiani M.R. (2016). Esercitazioni di Statistica. Terza edizione. Esculapio Editrice. In alternative, students can use other universitary handbooks of Statistics containing all the topics included into the programme.
Lesson mode
On-site classes.
  • Lesson code1015450
  • Academic year2024/2025
  • CourseBusiness sciences
  • CurriculumEconomia e commercio (corso serale)
  • Year2nd year
  • Semester1st semester
  • SSDSECS-S/01
  • CFU9
  • Subject areaStatistico-matematico