Statistics for Data Analysis (advanced)

A.Y. 2025/2026
6
Max ECTS
42
Overall hours
SSD
SECS-S/01 SECS-S/03
Language
Italian
Learning objectives
The course aims to provide a comprehensive set of theoretical and practical knowledge necessary for the systematic and accurate collection of data relevant to business economics. The course will cover various methodologies for data collection, including surveys, interviews, experiments, and the use of secondary sources. Additionally, the course aims to develop skills in applying the most appropriate statistical methods for analyzing these economic phenomena. This ensures that students can perform detailed and accurate analyses, correctly interpret the results obtained, and use this information to make informed and strategic business decisions.
Expected learning outcomes
By the end of the course, the student will have acquired an in-depth understanding of fundamental statistical concepts, including mean, median, mode, variance, and standard deviation, as well as the distinction between qualitative and quantitative variables and between discrete and continuous data. The student will be able to collect, organize, and analyze data from professional contexts, using data collection techniques such as surveys, experiments, and secondary sources, and representing the data in tables and graphs, such as histograms, bar charts, and scatter plots. Additionally, the student will develop skills in analyzing various types of data and performing statistical inferences, understanding the concepts of population and sample, sampling techniques, and gaining the ability to construct and interpret confidence intervals and hypothesis tests. Through learning data analysis techniques, students will be able to identify trends, make predictions, and contribute significantly to the decision-making process within organizations.
Single course

This course can be attended as a single course.

Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
Course syllabus
- Introduction to Statistics.
- Graphical description of data: classification of variables, frequency tables, and graphical representations.
- Numerical description of data: measures of central tendency and variability, summary measures for grouped data (covariance and correlation).
- Simple and multiple linear regression.
- Introduction to probability: definition of event, equally likely events, basic probability calculation, conditional probability, Bayes' theorem, independent events, discrete and continuous random variables.
- Statistical inference: estimation theory, estimators, sampling random variables, confidence intervals, hypothesis testing.
Prerequisites for admission
The course does not require prior knowledge of statistics, but a basic understanding of mathematics is recommended.
Teaching methods
Each topic in the syllabus will be presented theoretically during the lectures. For every topic, in addition to the theoretical part, the implementation using Excel will be shown. Particular attention will be devoted to the reading and interpretation of the obtained results.
Teaching Resources
- P. NEWBOLD-W.L. CARLSON-B.M. THORNE, Statistica, Pearson.
- Other materials on ARIEL website.
Assessment methods and Criteria
The examination consists of a production and discussion of a statistical report made by Word, regarding the analysis of a real data set. Especially, the report (5 or 6 pages long) should contain appropriate graphs, tables and synthesis indices obtained through use of excel, together with an interpretation of the analyzed phenomenon. An oral discussion follows for students that achieve a score of at least 18/30 in the production of the report, with the aim to assess the knowledge and understanding of the course subjects included in the report. Both production and discussion contribute to the final mark.
SECS-S/01 - STATISTICS - University credits: 3
SECS-S/03 - ECONOMIC STATISTICS - University credits: 3
Lessons: 42 hours
Professor: Facchinetti Silvia
Professor(s)