Learning objectives
This course aims to provide students with a solid understanding of statistical principles essential for proper interpretation of medical data. Students will develop skills in comprehending and interpreting correlation and concordance, recognizing their importance in assessing relationships between variables. The course will introduce the application of probability to diagnostic tests, emphasizing the fundamental role of these tests within the clinical diagnostic framework. Students will gain skills in evaluating the sensitivity, specificity, and predictive value of diagnostic tests, enabling them to make informed decisions regarding the accuracy and usefulness of these tests in diagnosing medical conditions. By understanding the statistical concepts underlying diagnostic testing, students will be equipped to critically assess and interpret test results, supporting evidence-based clinical decision-making. Lastly, practical skills in using Excel for data management and analysis will be introduced, allowing students to apply the learned statistical techniques within a medical context.
Prerequisites
No
Course unit content
The course is strictly related to medical statistics, which will proceed in parallel.
PROGRAM
• Correlation
o Definition and interpretation of correlation
o Calculation and interpretation of Pearson's correlation coefficient
o Practical examples of correlation
• Concordance
o Definition and utility of concordance
o Calculation of Cohen's K coefficient of concordance
o Applications of concordance in medicine
• Introduction to Probability
o Fundamental concepts of probability
o Calculation of simple and compound probabilities
o Bayes' theorem and its applications
• Probability Application to Diagnostic Tests
o Sensitivity, specificity, and predictive value
o Calculation and interpretation of diagnostic tests
o Receiver Operating Characteristic (ROC) curves and their interpretation
• Gaussian Model and Central Limit Theorem
o Concept of the normal or Gaussian distribution
o Properties and applications of the normal distribution
o Central Limit Theorem and its implications
• Confidence Intervals
o Introduction to confidence intervals
o Calculation and interpretation of confidence intervals
o Confidence interval for the mean and proportion
• Student-t Distribution
o Characteristics of the Student-t distribution
o Use of the Student-t distribution for small sample sizes
o t-tests for paired and unpaired means
• Hypothesis Testing for Categorical Variables
o Chi-square test for independence between categorical variables
o Fisher's test for the difference between proportions
• Data analysis with Excel
o Frequency tables and graphs appropriate for variable types
o Descriptive statistics
o Hypothesis Testing
o Chisquare test for categorical variables
Full programme
Contents include the extended program.
Bibliography
Classroom slides (uploaded during the course) and all the material on Elly are the reference point for the exam. Some further reference books: SA Glantz -
Statistica per discipline biomediche - McGraw-Hill. Any books covering Excel.
Teaching methods
This course is parallel to that of medical statistics. During the lessons, the course subject matter will be explained and commented. Each theoretical will be explained with simple and practical examples, so that students may focus on basic concepts more than on the formulae. The use of computers during the lessons is encouraged.
Lectures will be held on-site in compliance with safety standards, provided that further instructions on the ongoing health emergency are not implemented. Supporting material will be available on the specific, student-reserved platform (Elly) and will include slide presentations, audio-video aids or video-recording of the lectures.
Assessment methods and criteria
The evaluation of the students will be formative, as the aptitude test in medical statistics and data processing will be done in more than one step during the course. The tests will be at least two and will be performed by students on-line on Elly platform at fixed dates and hours or in a written form. If a student prefers a summative evaluation and/or does not pass the formative evaluation, he/she can do a final overall test on all the arguments treated during the course.
The exam will be done in presence or on-line (elly platform), depending on the pandemic course.
Other information
2030 agenda goals for sustainable development
