Statistics and management
Module Statistics for experimental and technological research

Academic Year 2025/2026 - Teacher: SALVATORE GIUSTINIANI

Expected Learning Outcomes

The student will acquire the statistical knowledge necessary to analyze data and prepare reports

Course Structure

interactive frontal lessons with exploration of practical examples

Detailed Course Content

Technical correlations and methodologies; Sampling methodologies and techniques for the extrapolation of a Significant sample, Number of a sample and errors that are made in analyzing a sample; Point estimates, confidence interval; Sime for large samples; small samples and Frequency, Analysis of the data obtained on the basis of acceptable errors; Hypothesis tests for large samples and frequency; Chi Square; Anova; some methods for non-parametric statistics. Concrete examples of data analysis in the health sector, drafting of statistical reports.

Textbook Information

Notes prepared by the teacher

Recommended book: Exploratory and Inferential Methods; M. Fraire, A. Rizzi; Carocci Editore


Course Planning

 SubjectsText References
1Correlation of methods and techniquesslide 1
2Sampling and sample size methods and techniquesslide 2
3point estimates and confidence intervalsslide 3
4Hypothesis Testing for Large, Small, and Frequency Samplesslide 4
5Chi quadroslide 5
6ANOVAslide 6
7methods and techniques for non-parametric samplesslide 7

Learning Assessment

Learning Assessment Procedures

Typical exercises on the topics of the program, with evaluation of the results obtained

Examples of frequently asked questions and / or exercises

We want to determine whether therapy A is more effective than therapy B given the following data:

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