Acquaint students with the basics of the experiment planning, measurement procedures and data analysis. Introducing fundamental concepts of metrology (measurement, uncertainty, etc.). Development of skills in application of the standard techniques used for data analysis (probability distribution, mean and standard deviation, regression, chi2 test.
Prerequisites
Knowledge of mathematics and physics at the secondary school level.
Scope
SI system. Base, derived and additioal units.
Number notation, significant figures, prefixes.
Classification of the measurement methods. Precise and accurate data.
Parent and sample population. Parameter and estimator.
Measurement uncertainty, statistical and systematic errors, data selection.
Parameters of the data distribution: mean, standard deviation, mode and median.
Propagation of errors.
Weighted mean.
Presentation of the measurement results, tables and figures.
Lagrange and Newton interpolation.
Probability distributions: binomial, Poisson, normal, Student, chi-square. Empirical distributions.
Regression and correlation.
Function fitting. Least-square method, chi-square test.
Guidelines for preparing the laboratory reports.
Teaching methods
Short lecture, classes, discussion, solving problems.
Learning outcomes and methods of theirs verification
Outcome description
Outcome symbols
Methods of verification
The class form
Assignment conditions
The final grade is a weighted mean of several elements:
- degree of being prepared for exercises (discussion, activity during the class): 25%,
- preparation of reports and homework solutions: 25%,
- final test: 50%.
Recommended reading
J.R. Taylor, An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements 2nd Edition, University Science Books, 1996.
P.R. Bevington, D.K. Robinson, Data Reduction and Error Analysis for the Physical Sciences, Third Edition, McGraw-Hill, 2003.
Further reading
S. Brandt, Data Analysis: Statistical and Computational Methods for Scientists and Engineers, 3rd Edition, Springer, 1998.
Notes
Modified by dr hab. Piotr Lubiński, prof. UZ (last modification: 27-10-2019 19:45)
