Experimental Physics

Recommended Prerequisites

The same as for the first year, first semester in the university.

Teaching Methods

Teaching methods: theoretical(15h), problem solving(15h) and experimental work(45h).

Learning Outcomes

Aquisition of basic concepts concerning data analysis of directly and indirectly measured properties: methods to make the best guess of the measured properties as well as of several functional correlation parameters between different physical properties; first principles of the fitting procedure based on minimizing the chi-squared.

Development of experimental and laboratorial competences. Use of a variety of instruments, with relevance to the identification of their characteristics and the origins of sistematic and random errors.

Competences of secondary importance: organization, planning and establishing methodological approaches; scientific communication; experimental data handling and computer representation.

Generic competences: analysis and synthesis; computer knowledge in the field of experimental data handling; working in group; critical reasoning; putting theory into practice; organization and planning; communication; problem solving; adaptability to new situations; research.

Work Placement(s)

No

Syllabus

True value of a physical property. Deviations of experimentally measured quantities. Propagation of the deviations.  Probability distributions. Minimum squares sum and maximum likelihood principles.

Best estimator of the true value of a physical property. Confidence intervals. Curve fitting of experimental data. Linear fits.

Evaluation of the quality of a given fit. Chi-squared test. Normalized chi-squared test.

Basic instrumentation notions: multimeter, oscilloscope, etc.

Performing experiments directly and indirectly measuring physical properties.

Applications to a variety of situations, including problem solving.

Assessment Methods

Assessment
Frequency: 20.0%
Laboratory work or Field work: 80.0%

Bibliography

CAMPOS, N. Ayres de. Introdução à análise de dados. Departamento de Física, U.C.

BEVINGTON, P.R. Data reduction and error analysis for the physical sciences. McGraw-Hill

BRANDT, Siegmund (1999). Data Analysis (3rd ed.). New York: Springer.