Ateneo - UPO

Analysis of experimental uncertainty in single and repeated measurements. Elements of probability and statistics.
Evaluation of confidence intervals on results. Linear ad non-linear regresion. Use of data analysis and presentation software.

Taylor J. R. Introduction To Error Analysis - second edition

The purpose of the course is to learn the basic techniques of data analysis and to use softwares like excel and R at a base level. The techniques learned can be used in everyday laboratory practice and in an experimental thesis. The acquired abilities are also useful for future teachers in secondary school.

During the lessons some simple derivatives and integrals will be used.

Presentation of measurements of biological interest. How to keep a laboraory logbook. Dicussion of experimental observations and data analysis with statistical software. Communication of results as a report.

It is essential to study the theory of data analysis before attending the lab. It is necessary to attend laboratory classes.
Students with physical disabilities, Learning Disabilities or Special Education Needs can request
specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse
e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-
students-physical-or-learning-disabilities
Students with disabilities, learning disabilities or special education needs, once they have contacted
the University Staff, can refer to the tutor in charge of the course to define the examination
modalities, concerning academic aspects.

The exam consist in a discussion of the written report of an experiment, of the theory of the data analysis techniques and an evaluation of the laboratory logbook.
The logbook shall enable to recall the experimental procedure even after a long time (with the description of eventual problems) and must report the collected data. The laboratory report and the slides must include: a synthetic description of the purpose of the experiments, the description of the experimenta materials and methods, report data with analysis and discussion of the results and of the eventual problems and possible updates of the procedures.
The exam is split in two sessions. A first session doesn't attribute marks and allows to identify potential problems and improvements in the material. In the actual exam the updated work is discussed.
The exams dates are agreed with the teacher.

Measurement and experimental errors. Analysis of random errors: average, standard deviation, error on mean. Error propagation. Probability distributions. Confidence intervals. Linear and non-linear regression.
Physical measurements of biological interest will be proposed, for example: calibration of a micropipette and a graduated cylinder, counting measurements, analysis of perception thresholds,. image analysis with ImageJ, measurements on an electrical model of a neuron.

Knowledge and understanding: awareness of the existence of experimental uncertainties. Knowledge of the techniques to quantify them.
Applying knowledge and understanding: apply these techniques in a simple experimental context. Use of data analysis programs at a basic level.
Communication skills: ability to communicate experimental results in written form and in oral presentation.