Physics, statistics and computer science 4Module Medical statistics
Academic Year 2025/2026 - Teacher: CESARE GAROFALOExpected Learning Outcomes
The course aims to introduce the student to the elementary principles of statistics applied to medicine and epidemiology. Students will acquire knowledge of the main models, indices and statistical tests to apply them to the qualitative and quantitative description of real cases.
Students will also acquire the ability to learn and study medical statistics topics independently.
Students will also acquire the ability to learn and study medical statistics topics independently.
Course Structure
Frontal lessons.
Attendance of Lessons
Obbligatoria
Detailed Course Content
Statistics and science methodology: causation, statistical correlation and biases.
Determinants of the variability of biological, clinical and laboratory data.
Numerical calculation reminders. Numbers in scientific notation. Percentages. Data normalization. Combinatorial calculus. Data collection and organization. Types of variables.
Position indices: arithmetic mean, geometric mean, harmonic mean, mode, median, quartiles, percentiles.
Dispersion indices: range of variation, deviance, variance, standard deviation, coefficient of variation.
Graphical representation
Combinatorial calculus. Calculation of probabilities and probability distributions.
The standardized normal distribution.
Sampling and statistical inference.
Statistical significance tests: null hypothesis, type I and type II error, level of significance, p-value, power of a statistical test.
Student's t-test for paired and unpaired data
Chi-square test.
Correlation: Bravais-Pearson index. Cramer index. Relative risk.
Regression.
Derivation ratios. Morbidity, mortality, lethality, incidence and prevalence rates.
Experimental and observational studies.
Evaluation of screening and diagnostic tests: sensitivity, specificity, predictive value, efficiency.
Hospital indicators and indices: structure, use, rotation, outcome indicators.
Determinants of the variability of biological, clinical and laboratory data.
Numerical calculation reminders. Numbers in scientific notation. Percentages. Data normalization. Combinatorial calculus. Data collection and organization. Types of variables.
Position indices: arithmetic mean, geometric mean, harmonic mean, mode, median, quartiles, percentiles.
Dispersion indices: range of variation, deviance, variance, standard deviation, coefficient of variation.
Graphical representation
Combinatorial calculus. Calculation of probabilities and probability distributions.
The standardized normal distribution.
Sampling and statistical inference.
Statistical significance tests: null hypothesis, type I and type II error, level of significance, p-value, power of a statistical test.
Student's t-test for paired and unpaired data
Chi-square test.
Correlation: Bravais-Pearson index. Cramer index. Relative risk.
Regression.
Derivation ratios. Morbidity, mortality, lethality, incidence and prevalence rates.
Experimental and observational studies.
Evaluation of screening and diagnostic tests: sensitivity, specificity, predictive value, efficiency.
Hospital indicators and indices: structure, use, rotation, outcome indicators.
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | Statistics and methodology of science: causation, statistical correlation and biases. Determinants of variability in biological, clinical and laboratory data. | |
| 2 | Numerical calculation reminders. Numbers in scientific notation. Percentages. Data normalization. Data collection and organization. | |
| 3 | Position indices: arithmetic mean, geometric mean, harmonic mean, mode, median, quartiles, percentiles. | |
| 4 | Indices of dispersion: range of variation, deviance, variance, standard deviation, coefficient of variation. | |
| 5 | The graphic representation | |
| 6 | Combinatorial calculus. Probability calculus and probability distributions. The standardized normal distribution. | |
| 7 | Sampling and statistical inference. Tests of statistical significance: null hypothesis, type I and type II errors, significance level, p-value, power of a statistical test. Student's t-test for paired and unpaired data. Chi-square test. Correlation: Bravais-Pearson index. Cramer index. Relative risk. Regression. | |
| 8 | Derivation ratios. Morbidity, mortality, lethality, incidence and prevalence rates. Experimental and observational studies. | |
| 9 | Evaluation of screening and diagnostic tests: sensitivity, specificity, predictive value, efficiency. Hospital indicators and indices: structure, use, rotation, outcome indicators. |
Learning Assessment
Learning Assessment Procedures
The candidate's written test will be evaluated on the correctness of the procedures performed and on the clarity of the presentation.
Examples of frequently asked questions and / or exercises
What is the probability that an individual, randomly selected from a population with mean weight of 73 kg and standard deviation 13 kg, weighs between:
a) 60 and 80 kg?
b) 74 and 80 kg?
VERSIONE IN ITALIANO
a) 60 and 80 kg?
b) 74 and 80 kg?
c) 66 and 70 kg?
To verify the effectiveness of a new diet aimed at losing weight, 10 volunteers underwent treatment for 3 months. The table below shows the weights in kg of the patients before and after the diet.
Can we say that the diet is effective?
Participant 1 2 3 4 5 6 7 8 9 10
Before 80 85 90 75 88 82 78 92 84 79
After 78 83 87 74 85 80 76 89 82 77
Determine whether the results obtained in department (A) can be considered different from those of department (B):
Recovered Improved Stable Worsened Total
Department (A) 20 14 7 9 50
Department (B) 32 13 8 12 65
Total 52 27 15 21 115