AIMS AND CONTENT

AIMS AND LEARNING OUTCOMES

Acquire fundamental concepts and methodologies in biometry and statistics to collect, describe, interpret, and critically evaluate information and understand biomedical phenomena.

TEACHING METHODS

Students with valid certifications for Specific Learning Disorders (DSA), disabilities, or other educational needs are encouraged to contact the instructor and the disability coordinator of the School/Department at the beginning of the course. This is to agree on any teaching methods that, while respecting the course objectives, take into account individual learning modalities.

SYLLABUS/CONTENT

1. Variability in Biological, Clinical, and Laboratory Data, Measurement Errors

• Understand the sources and implications of variability in data.
• Identify and manage different types of measurement errors.

2. Statistical Nature of Observations

• Recognize and describe the statistical properties of data observations.

3. Absolute, Relative, and Percentage Frequencies

• Calculate and interpret absolute, relative, and percentage frequencies.

4. Data Collection, Organization, and Representation

• Develop skills for systematic data collection and organization.
• Learn various methods of data representation for clear communication of findings.

5. Data Synthesis: Measures of Central Tendency and Dispersion

• Calculate measures of central tendency: mean, median, mode, and quantiles.
• Assess data variability through measures of dispersion such as range, variance, and standard deviation.

6. Introduction to Probability Calculations

• Understand basic probability concepts, including conditional probability and independence.
• Apply the principles of addition and multiplication in probability calculations.

7. Probability Distributions: Gaussian Distribution

• Explore the properties and applications of the Gaussian (normal) distribution.

8. Fundamentals of Statistical Inference

• Differentiate between populations and samples.
• Construct and interpret confidence intervals for means and percentages.

9. Statistical Evaluations in Diagnostic Test Classification

• Evaluate diagnostic tests using statistical methods.

10. Hypothesis Testing and Regression Models - Conduct hypothesis tests and understand their implications. - Explore the basics of statistical regression models.

11. Research Methodology - Learn the essential elements of research methodology. - Design and analyze various types of research studies, including randomized controlled trials.

12. Systematic Reviews and Meta-Analyses - Understand the principles and methods of conducting systematic reviews and meta-analyses to synthesize research findings.

This curriculum is designed to equip students with the essential statistical tools and methodologies necessary for biomedical research, enabling them to critically evaluate and interpret data within the context of scientific studies.

RECOMMENDED READING/BIBLIOGRAPHY

Recommended text: Martin Bland - Medical Statistics

However, all material uploaded on Aulaweb is sufficient.

TEACHERS AND EXAM BOARD

Exam Board

ROSAGEMMA CILIBERTI (President)

STEFANIA ISOLABELLA

MASSIMO MARESCA

MARIA PIA SORMANI

ALESSIO SIGNORI (President and Coordinator of Integrated Course)

LESSONS

LESSONS START

Lessons will start the first week of October

EXAMS

EXAM DESCRIPTION

The assessment of learning will be conducted in written form, consisting of multiple-choice quizzes and open-ended questions, as part of the examination for the Integrated Course that includes the discipline "Medical Statistics."

ASSESSMENT METHODS

The student must demonstrate a knowledge of both descriptive and inferential statistics, and their proficiency will be assessed through exercises presented during the exam.

Exam schedule