Insegnamento a.a. 2024-2025

The course covers the following topics:

• Collection, management and summary of data using frequency distributions, graphical representations and summaries.
• Study of the relationship between two variables.
• Statistical inference and sampling variability.
• Theory of point estimation and confidence intervals.
• Hypothesis testing.
• Simple and multiple regression models

Note that all the descriptive and inferential tools introduced during the course will be applied to data using the statistical software R - and in particular the integrated development environment (IDE) RStudio. Therefore some lessons will be dedicated to the software.

• Recognize different types of data.
• Understand the difference between the tools of descriptive and inferential statistics, and identify the most suitable approach for the problem at hand.
• Recognize simple statistical models.

• Properly summarize a dataset.
• Estimate, and test hypotheses on, the unknown parameters of a population on the basis of sample data.
• Build simple and multiple regression models to study the relationships  between variables of interest.
• Use the R software to address the aforementioned issues.

• Lectures
• Practical Exercises

Beyond traditional classes, the course features hands-on classes, where the statistical software R - and in particular the integrated development environment (IDE) RStudio - is used to apply basic statistical analyses to data. More specifically, during these sessions students will use their laptop to address specific issues, and to interpret the obtained results.

The assessment method is based on a written exam; students will answer theoretical questions, solve traditional “paper and pencil” derivation exercises (questions based on aggregated data), report and comment the results obtained by analysing data using the software R/Rstudio

The exam aims at assessing:

• The understanding of the statistical tools introduced and used in the course
• The ability to identify the proper methodology to solve a given problem.
• The understanding of the logic underlying a certain procedure.
• The ability to compute appropriate statistical measures with both a pocket calculator and a statistical software.
• The ability of suggesting and implementing with R a statistical model, consistent with both the assumptions stated and the data at hand.
• The ability to understand the software output.

All the students, both those attending and not attending, as well as students in debt, can take the exam in two ways.

1. It is possible to take two midterm exams, each graded with maximum 31 points. Each midterm is passed with a grade higher or equal to 15. If both the midterms are passed, the final grade is the average of the points taken in the midterms. A final grade higher than or equal to 30.5 is rewarded cum laude.
   Important: only students who passed the first midterm can take the second midterm. Students who pass both the midterm with a grade lower than 18 in the second midterm  can ask to have their final grade not registered. This does not hold for students whose grade in the first midterm is lower than 18, because sitting for the second midterm implies acceptance of the grade in the first midterm.
2. Alternatively, student can take a final general exam, graded with 31/30 points maximum. The exam is passed with a grade higher than or equal to 18. A final grade equal to 31 is rewarded cum laude.

To encourage the participation to lessons, students who

a) attend at least the 75% of the lessons in the first part of the course (before the first midterm)

and b) attend at least the 75% of the lessons in the second part of the course

and c) pass the exam in the sessions of January or February

will have 1 additional added to their final grade (average of the grades in the two midterms or grade taken in the general exam). Please note that such additional point does not contribute to the laude.

Students who improperly register their attendance – besides the consequences stated in the Honor Code – will unquestionably lose this additional point. Same holds for students who carry out other activities during the lessons and/or who disturb during the lessons. An active and attentive participation to lessons is requested.

• P. NEWBOLD, W.L. CARLSON, B. THORNE, Statistics for Business and Economics, Pearson/Prentice Hall, 9th global edition (2019). 

• Additional material integrating the textbook,  available on the Bboard platform.

• Additional material on R/Studio available on the Bboard platform.