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B011411 - MEDICAL STATISTICS
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Type of Assessment
Course program
Academic Year 2019-20
Coorte 2019 - 6-years Single Cycle Degree in MEDICINA E CHIRURGIA
Course year
First year - First Semester
Belonging Department
Experimantal and Clinical Medicine
Modulo di sola Frequenza of
Scientific Area
MED/01 - MEDICAL STATISTICS
Credits
1
Teaching Hours
12
Teaching Term
23/09/2019 ⇒ 17/01/2020
Attendance required
Yes
Type of Evaluation
Giudizio Finale
Course Content
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Course program
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Lectureship
- Part A BIGGERI ANNIBALE
- Part B BACCINI MICHELA
Teaching Language - Part A
italian
Teaching Language - Part B
Italian
Course Content - Part A
Probability calculus. Bayes Theorem and Diagnosis. Test sensibility and specificity; predictive values. Binomial; Poisson; Gauss distributions. Descriptive statistics
Course Content - Part B
Basic principles of probability and descriptive statistics.
Suggested readings - Part A (Search our library's catalogue)
Bland Medical Statistics Oxford University Press
Pagano et al. Biostatistics McGraw-Hill
Pagano et al. Biostatistics McGraw-Hill
Suggested readings - Part B (Search our library's catalogue)
Bland M. An Introduction to Medical Statistics. Oxford University Press.
- Pagano et al. Principles of Biostatistics. Duxbury Pr.
- Pagano et al. Principles of Biostatistics. Duxbury Pr.
Learning Objectives - Part A
basic notions and methods of statistics useful to understand and interpret
biological phenomena
biological phenomena
Learning Objectives - Part B
To provide basic tools for analysis and understanding of biomedical data.
Prerequisites - Part A
none
Prerequisites - Part B
None
Teaching Methods - Part A
lecture, practicals
Teaching Methods - Part B
Lectures and practicals.
Type of Assessment - Part A
written examination
Type of Assessment - Part B
written examination
Course program - Part A
Probability calculus. Bayes Theorem and Diagnosis. Test sensibility and specificity; predictive values. Binomial; Poisson; Gauss distributions. Descriptive statistics
Course program - Part B
- Probability and Odds.
- Bayes Theorem
- Diagnostic test, sensitivity, specificity, predictive values.
- Binomial, Poisson and Gaussian distributions.
-Descriptive statistics.
- Bayes Theorem
- Diagnostic test, sensitivity, specificity, predictive values.
- Binomial, Poisson and Gaussian distributions.
-Descriptive statistics.