The objective of this course is to allow a correct choice of statistical tools both in descriptive statistics and in inferential one.

Mathematics

1. Combinatorics 

1.1 Fundamental principle of combinatorics

1.2 Dispositions, permutations and combinations without repetitions 

1.3 Dispositions, permutations and combinations with repetitions

2. Probability

2.1 Definitions of probability (classical, frequency, subjective, axiomatic probability)

2.2 Addition and multiplication rules for probability

2.3 Conditional probability; Bayes' theorem

1. Descriptive Statistics

1.1 Population, sample, sampling

1.2 Variables and their classification

1.3 Means (arithmetic mean, median, mode)

1.4 Indexes of variability (range, variance, standard deviation, coefficient of variation)

1.5 Correlation and regressions

2. Inferential Statistics

2.1 General principles

2.2 Statistical distributions: Gaussian Normal, Standardized Gaussian Normal, Sample mean distribution, Student's t distribution

2.3 Significance Test: z-test, t-test

2.4 Confidence Intervals for means and proportions

3. Statistical topics in phase III Protocol

3.1 Protocols

3.2 Experimental design (between patients, within patients, factorial)

3.3 Randomization techniques

3.4 Sample size

3.5 Ad interim analyses

3.6 Critical analysis of clinical trials and experimental literature

None

In relation to Statistics and Mathematics, the student should show possession of: 

- the mastery of basic skills; 

- the understanding of the fundamental concepts of the discipline 

- the ability to use knowledge and concepts to reason according to the logic of the discipline.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Seminars; guided exercises 

The teaching material and specific communications from the lecturer can be found, together with other supporting activities, inside the Moodle platform › blended.uniurb.it

Teaching

 Frontal lessons; guided exercises

Attendance

None; participation is strongly recommended

Course books

Rocchi MBL: Statistica e metodologia della ricerca per le discipline biomediche e psicocomportamentali, Edizioni Goliardiche, Trieste, 2007 (pag. 250)

Assessment

Written test. Oral exam ( after passing the written test )

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

the material available on blended.uniurb.it can be advantageously used

Attendance

None

Course books

As for attending students

Assessment

As for attending students

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.