30001 - STATISTICA / STATISTICS
Dipartimento di Scienze delle Decisioni / Department of Decision Sciences
Per la lingua del corso verificare le informazioni sulle classi/
For the instruction language of the course see class group/s below
RAFFAELLA PICCARRETA
Class 15: PIERALBERTO GUARNIERO, Class 16: MARTA ANGELICI, Class 17: DANIELE TONINI, Class 18: EMILIO GREGORI
Class group/s taught in English
Suggested background knowledge
PREREQUISITES
Mission & Content Summary
MISSION
CONTENT SUMMARY
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 regression model and brief introduction to the multiple regression model.
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- 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.
APPLYING KNOWLEDGE AND UNDERSTANDING
- Properly summarize a dataset.
- Estimate, and test hypotheses on, the unknown parameters of a population on the basis of sample data.
- Build simple statistical models, as regression models, aimed at studying the relationships between variables of interest.
- Use the R software to address the aformentioned issues.
Teaching methods
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Case studies /Incidents (traditional, online)
DETAILS
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.
Assessment methods
Continuous assessment | Partial exams | General exam | |
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x | x |
ATTENDING AND NOT ATTENDING STUDENTS
The assessment method, both for attending and not-attending students, consists of 1) two midterm exams or 2) a general exam.
The two midterms are articulated into two parts. The first part, consisting in a traditional written exam with theoretical questions and traditional “paper and pencil” derivation exercises, is graded 26 points maximum. The second part consists of the analysis of a dataset using R/Rstudio (installed on each student’s laptop), and is graded 5 points maximum. The maximum grade in each midterm is 31/30.
To pass the exam, a grade higher than or equal to 15 is required in both midterms, and an average of at least 18 points. A final grade equal to 31 is rewarded cum laude.
The general exam is organized as the midterms, and consists of a first traditional part (theoretical questions and “paper and pencil” exercises) graded 26 points maximum, and of a second part with problems to be solved using R/Rstudio (installed on each student’s laptop), graded 5 points maximum. The maximum grade in the exam is 31/30; The exam is passed with a grade higher than or equal to 18. A final grade equal to 31 is rewarded cum laude.
The exam aims at assessing:
- 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.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
- P. NEWBOLD, W.L. CARLSON, B. THORNE, Statistics for Business and Economics, Pearson/Prentice Hall, 9th global edition (2019).
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Additional teaching note on Frequency Distributions, available on the Bboard platform.
- A specific manual on the use of R/Studio available on the Bboard platform.