Physics, Physics Lab, Lab of Mathematical and Statistical Methodologies
A.Y. 2024/2025
Learning objectives
The aim of the course is to provide students with the physical and statistical background needed for the quantitative understanding of biological phenomena. Furthermore, it will provide the knowledge of the physical principles behind many lab instruments as well as the statistical tools to correctly interpret experiments.
Expected learning outcomes
After following this course, the students will know the fundamental principles of classical physics and statistics. The students will know how to apply them to solve simple problems and how to quantitatively approach the biosciences.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
A - L
Responsible
Lesson period
Second semester
Prerequisites for admission
Have attended the basic course on calculus of the first semester.
Assessment methods and Criteria
The student is required to pass a separate test for each of the 3 modules. The module Physics requires a final written test and an oral one; the written test can be substituted by 2 tests taken during the lesson time. The Laboratory module requires a preformatted relation at the end of the laboratory activities, and a written test with exercises on the subjects of the program. The evaluation is the arithmetic mean of the laboratory and written test evaluations. The Statistics module requires a written test with exercises of probability and statistics and questions about the theoretical aspects.
The exam registration can only be done after having passed all modules.
The exam registration can only be done after having passed all modules.
Modulo: Fisica
Course syllabus
Kinematics: linear and curved motions
Dynamics for the material point: principles and forces
Energy: work and energy conservation
Collisions: linear moment, elastic and anelastic collisions
Electrostatics: Coulomb force, electric field and potential, capacitor, Lorentz force.
Fluids: Static and dynamics of an ideal fluid, Laws of Pascal, Stevino, Archimede and Bernoulli.
Thermodynamics: Principles, ideal gases law, kinetic theory of an ideal gases, heat capacity, phase transitions, thermodynamics transformations, heat engines.
Dynamics for the material point: principles and forces
Energy: work and energy conservation
Collisions: linear moment, elastic and anelastic collisions
Electrostatics: Coulomb force, electric field and potential, capacitor, Lorentz force.
Fluids: Static and dynamics of an ideal fluid, Laws of Pascal, Stevino, Archimede and Bernoulli.
Thermodynamics: Principles, ideal gases law, kinetic theory of an ideal gases, heat capacity, phase transitions, thermodynamics transformations, heat engines.
Teaching methods
Lectures and tutorials using the blackboard
Teaching Resources
Suggested reading:
R. A. Serway, J. W. Jewett, "Principi di Fisica", EdiSES.
A Alessandrini, "Fisica per scienze della vita", Casa editrice Ambrosiana (Zanichelli).
Additional exercises and exams examples will be available via Ariel.
R. A. Serway, J. W. Jewett, "Principi di Fisica", EdiSES.
A Alessandrini, "Fisica per scienze della vita", Casa editrice Ambrosiana (Zanichelli).
Additional exercises and exams examples will be available via Ariel.
Modulo: Laboratorio di Fisica
Course syllabus
The course is partly lessons and partly laboratory. Lessons cover a short practical introduction to applied statistics and physics complements. the physics subjects treated are: electrical circuits (RC included); mechanical waves and electromagnetic waves spectrum, geometrical optics and elements of physical optics, elements of radioactivity.
The result of the laboratory is the measurement of the Faraday constant, with 2 different methods, of which precision, accuracy and compatibility are evaluated.
The result of the laboratory is the measurement of the Faraday constant, with 2 different methods, of which precision, accuracy and compatibility are evaluated.
Teaching methods
Lessons supported by projected material.
Attendance is strongly recommended for the lessons and is compulsory for the activities in laboratory
Attendance is strongly recommended for the lessons and is compulsory for the activities in laboratory
Teaching Resources
R. A. Serway, J. W. Jewett "Principi di Fisica" EdiSES
Analisi degli errori sperimentali di laboratorio; L. Miramonti, L. Perini, I. Veronese; EdiSES
Analisi degli errori sperimentali di laboratorio; L. Miramonti, L. Perini, I. Veronese; EdiSES
Modulo: Laboratorio di metodi matematici e statistici
Course syllabus
Descriptive statistics.
Population sampling. Types of data and variables. Subdivision of data into classes and creation of frequency tables. Histogram and histogram/bars. Centrality indexes (mean, mode, median, midrange), dispersion indexes (range, standard deviation, variance), percentiles, quartiles. Outliers. Boxplots.
Probability and random variables.
Sample space, events, probability of events. Probability of union and intersection of events. Complementary events. Independent events. Conditional probability. Bayes theorem. Factorial and binomial coefficients. Random variables. Expected value, variance, and standard deviation of discrete random variables. Discrete random variables: binomial and Poisson. Continuous random variables: uniform and normal. Standardization and calculations with the normal distribution. Percentiles. Normal approximation of binomial distribution.
Inferential statistics.
Fundamental concepts: population, sample, parameters, statistics, estimators. Sample mean behavior: large number law and central limit theorem. Confidence interval: general concepts. Confidence interval for a proportion. Confidence interval for the mean, both with known and unknown standard deviation. Student's distribution. Hypothesis test. General concepts: null and alternative hypothesis, first and second kind errors, significativity level, power function, p-value, statistics of the test, critical region. Test on the proportion. Test on the mean (both with known and unknown variance). Inference on two samples. Inference on two proportions. Inference on two means, both for independent and paired samples.
Linear regression and non-parametric procedures.
Covariance and correlation. Simple linear regression. Test on regression coefficients and model validation. Chi-square distribution. Test of independence and good adaptation.
Population sampling. Types of data and variables. Subdivision of data into classes and creation of frequency tables. Histogram and histogram/bars. Centrality indexes (mean, mode, median, midrange), dispersion indexes (range, standard deviation, variance), percentiles, quartiles. Outliers. Boxplots.
Probability and random variables.
Sample space, events, probability of events. Probability of union and intersection of events. Complementary events. Independent events. Conditional probability. Bayes theorem. Factorial and binomial coefficients. Random variables. Expected value, variance, and standard deviation of discrete random variables. Discrete random variables: binomial and Poisson. Continuous random variables: uniform and normal. Standardization and calculations with the normal distribution. Percentiles. Normal approximation of binomial distribution.
Inferential statistics.
Fundamental concepts: population, sample, parameters, statistics, estimators. Sample mean behavior: large number law and central limit theorem. Confidence interval: general concepts. Confidence interval for a proportion. Confidence interval for the mean, both with known and unknown standard deviation. Student's distribution. Hypothesis test. General concepts: null and alternative hypothesis, first and second kind errors, significativity level, power function, p-value, statistics of the test, critical region. Test on the proportion. Test on the mean (both with known and unknown variance). Inference on two samples. Inference on two proportions. Inference on two means, both for independent and paired samples.
Linear regression and non-parametric procedures.
Covariance and correlation. Simple linear regression. Test on regression coefficients and model validation. Chi-square distribution. Test of independence and good adaptation.
Teaching methods
The course is held through lectures mainly on the blackboard.
The student is encouraged to ask questions, to participate actively in the class discussion to improve his / her logical-analytical reasoning skills, to take a scientific and critical attitude to problems with uncertainty aspects, to use the precise technical language of the matter as well as its specific methodologies for solving statistical problems.
The student is encouraged to ask questions, to participate actively in the class discussion to improve his / her logical-analytical reasoning skills, to take a scientific and critical attitude to problems with uncertainty aspects, to use the precise technical language of the matter as well as its specific methodologies for solving statistical problems.
Teaching Resources
Text: Sheldon Ross, Probabilità e statistica per l'ingegneria e le scienze (terza edizione), Maggioli Editore (2015)
Modulo: Fisica
FIS/07 - APPLIED PHYSICS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Ferraro Alessandro
Modulo: Laboratorio di Fisica
FIS/06 - PHYSICS OF THE EARTH AND OF THE CIRCUMTERRESTRIAL MEDIUM - University credits: 3
Practicals: 32 hours
Laboratories: 16 hours
Laboratories: 16 hours
Professors:
Migliorini Lorenzo, Paroli Bruno
Shifts:
Professor:
Paroli Bruno
Turno 2
Professor:
Paroli BrunoTurno 3
Professor:
Migliorini LorenzoTurno1
Professor:
Paroli Bruno
Modulo: Laboratorio di metodi matematici e statistici
MAT/06 - PROBABILITY AND STATISTICS - University credits: 2
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
Laboratories: 32 hours
Lessons: 8 hours
Lessons: 8 hours
Professors:
Campi Luciano, Villa Elena
M - Z
Responsible
Lesson period
Second semester
Prerequisites for admission
Have taken the first-semester basic calculus course.
Assessment methods and Criteria
The student must pass a separate test for each of the 3 modules. The Physics module requires a final written test and an oral test; the written test can be replaced by 2 tests taken during the course. The Laboratory module requires a pre-formatted relation at the end of the laboratory activities and a written test with exercises on the topics of the program. The grade is the arithmetic mean of the laboratory and written test scores. The Statistics module requires a written test with exercises on probability and statistics and questions on theoretical aspects.
Registration for the exam can be done only after passing all modules.
Registration for the exam can be done only after passing all modules.
Modulo: Fisica
Course syllabus
Kinematics: linear and curved motions
Dynamics for the material point: principles and forces
Energy: work and energy conservation
Collisions: linear moment, elastic and anelastic collisions
Electrostatics: Coulomb force, electric field and potential, capacitor, Lorentz force.
Fluids: Static and dynamics of an ideal fluid, Laws of Pascal, Stevino, Archimede and Bernoulli.
Thermodinamics: Principles, ideal gases law, kinetic theory of an ideal gases, heat capacity, phase transitions, thermodynamics transformations, heat engines.
Dynamics for the material point: principles and forces
Energy: work and energy conservation
Collisions: linear moment, elastic and anelastic collisions
Electrostatics: Coulomb force, electric field and potential, capacitor, Lorentz force.
Fluids: Static and dynamics of an ideal fluid, Laws of Pascal, Stevino, Archimede and Bernoulli.
Thermodinamics: Principles, ideal gases law, kinetic theory of an ideal gases, heat capacity, phase transitions, thermodynamics transformations, heat engines.
Teaching methods
Lectures and exercises on the blackboard
Teaching Resources
R. A. Serway, J. W. Jewett "Principi di Fisica" EdiSES
Alessandrini, "Fisica per le scienze della vita", Casa Editrice Ambrosiana
additional notes, exercises and exams examples are available on Ariel.
Alessandrini, "Fisica per le scienze della vita", Casa Editrice Ambrosiana
additional notes, exercises and exams examples are available on Ariel.
Modulo: Laboratorio di Fisica
Course syllabus
The course is partly lessons and partly laboratory. Lessons cover a short pratical introduction to applied statistics and physics complements. the physics subjects treated are: electrical circuits (RC included); mechanical waves and electomagnetical waves spectrum, geometrical optics and elements of physical optics, elements of radioactivity.
The final result of the laboratory is the measurement of the Faraday constant, with 2 different methods, of which precision, accuracy and compatibility are evaluated.
The final result of the laboratory is the measurement of the Faraday constant, with 2 different methods, of which precision, accuracy and compatibility are evaluated.
Teaching methods
Lessons supported by projected material.
Attendance is strongly recommended for the lessons and is compulsory for the activities in laboratory
Attendance is strongly recommended for the lessons and is compulsory for the activities in laboratory
Teaching Resources
R. A. Serway, J. W. Jewett "Principi di Fisica" EdiSES
Analisi degli errori sperimentali di laboratorio; L. Miramonti, L. Perini, I. Veronese; EdiSES
Analisi degli errori sperimentali di laboratorio; L. Miramonti, L. Perini, I. Veronese; EdiSES
Modulo: Laboratorio di metodi matematici e statistici
Course syllabus
Descriptive statistics.
Population sampling. Types of data and variables. Subdivision of data into classes and creation of frequency tables. Histogram and histogram/bars.Centrality indexes (mean, mode, median, midrange), dispersion indexes (range, standard deviation, variance), percentiles, quartiles. Outliers. Boxplots.
Probability and random variables.
Sample space, events, probability of events. Probability of union and intersection of events. Complementary events. Independent events. Conditional probability. Bayes theorem. Factorial and binomial coefficients. Random variables. Expected value, variance and standard deviation of discrete random variables. Discrete random variables: binomial and Poisson. Continuous random variables: uniform and normal. Standardization and calculations with the normal distribution. Percentiles. Normal approximation of binomial distribution.
Inferential statistics.
Fundamental concepts: population, sample, parameters, statistics, estimators. Sample mean behavior: large number law and central limit theorem. Confidence interval: general concepts. Confidence interval for a proportion. Confidence interval for the mean, both with known and unknown standard deviation. Student's distribution. Hypothesis test. General concepts: null and alternative hypothesis, first and second kind errors, significativity level, power function, p-value, statistics of the test, critical region. Test on the proportion. Test on the mean (both with known and unknown variance). Inference on two samples. Inference on two proportions. Inference on two means, both for independent and paired samples.
Linear regression and non-parametric precedures.
Covariance and correlation. Simple linear regression. Test on regression coefficients and model validation. Chi-square distribution. Test of independence and good adaptation.
Population sampling. Types of data and variables. Subdivision of data into classes and creation of frequency tables. Histogram and histogram/bars.Centrality indexes (mean, mode, median, midrange), dispersion indexes (range, standard deviation, variance), percentiles, quartiles. Outliers. Boxplots.
Probability and random variables.
Sample space, events, probability of events. Probability of union and intersection of events. Complementary events. Independent events. Conditional probability. Bayes theorem. Factorial and binomial coefficients. Random variables. Expected value, variance and standard deviation of discrete random variables. Discrete random variables: binomial and Poisson. Continuous random variables: uniform and normal. Standardization and calculations with the normal distribution. Percentiles. Normal approximation of binomial distribution.
Inferential statistics.
Fundamental concepts: population, sample, parameters, statistics, estimators. Sample mean behavior: large number law and central limit theorem. Confidence interval: general concepts. Confidence interval for a proportion. Confidence interval for the mean, both with known and unknown standard deviation. Student's distribution. Hypothesis test. General concepts: null and alternative hypothesis, first and second kind errors, significativity level, power function, p-value, statistics of the test, critical region. Test on the proportion. Test on the mean (both with known and unknown variance). Inference on two samples. Inference on two proportions. Inference on two means, both for independent and paired samples.
Linear regression and non-parametric precedures.
Covariance and correlation. Simple linear regression. Test on regression coefficients and model validation. Chi-square distribution. Test of independence and good adaptation.
Teaching methods
The course is held through lectures mainly on the blackboard.
The student is encouraged to ask questions, to participate actively in the class discussion to improve his / her logical-analytical reasoning skills, to take a scientific and critical attitude to problems with uncertainty aspects, to use the precise technical language of the matter as well as its specific methodologies for solving statistical problems.
The student is encouraged to ask questions, to participate actively in the class discussion to improve his / her logical-analytical reasoning skills, to take a scientific and critical attitude to problems with uncertainty aspects, to use the precise technical language of the matter as well as its specific methodologies for solving statistical problems.
Teaching Resources
Sheldon Ross, Probabilità e statistica per l'ingegneria e le scienze (terza edizione), Maggioli Editore (2015)
Modulo: Fisica
FIS/07 - APPLIED PHYSICS - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Camilloni Carlo
Modulo: Laboratorio di Fisica
FIS/06 - PHYSICS OF THE EARTH AND OF THE CIRCUMTERRESTRIAL MEDIUM - University credits: 3
Practicals: 32 hours
Laboratories: 16 hours
Laboratories: 16 hours
Professor:
Miramonti Lino
Shifts:
Professor:
Miramonti Lino
Turno 1
Professor:
Miramonti LinoTurno 2
Professor:
Miramonti Lino
Modulo: Laboratorio di metodi matematici e statistici
MAT/06 - PROBABILITY AND STATISTICS - University credits: 2
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
Laboratories: 32 hours
Lessons: 8 hours
Lessons: 8 hours
Professor(s)
Reception:
15:00
Physics Department "Aldo Pontremoli" (Via G. Celoria, 16) - Dynamic Scattering Laboratory