Course code 07 53 1105 30
ECTS credits 3
Course name in language of instruction 
Metody analizy danych doświadczalnych I
Course name in Polish Metody analizy danych doświadczalnych I
Course name in English 
Experimental Data Analysis I
Language of instruction Polish
Form of classes
Teaching hours per semester
Lecture Tutorials Laboratory Project Seminar Other E-learn.
Contact hours 15 15 15
Distance learning No No No No No No No
Weighted grades 0.30 0.40 0.30
Unit running the course Instytut Fizyki
Course coordinator dr inż. Ewa Pastorczak
Course instructors dr inż. Ewa Pastorczak
Prerequisites 
Familiarity with the probability calculus
Course learning outcomes
  1. The student should be able to design and prepare an experimental setup in an optimal way.
  2. The student should be able to correctly carry out simple measurements.
  3. The student should be able to identify the sources of measurement uncertainty and estimate their influence on the results.
  4. The student should be able to correctly gather and present the results of the measurements.
  5. The student should be able to carry out a simple statistical analysis of his/her measurement results, including correlation analysis, and apply the least squares' method.
  6. The student should be familiar with basis notions in statistics.
Assessment methods 1. Observation of students' work during the laboratory part (effects 1 and 2) 2. Reports from the laboratory exercises (effects 3,4,5) 3. A test consisting of theoretical questions and problems to solve (effects 1,3,5,6)
Programme learning outcomes
  1. knowledge of selected methods for the analysis of experimental data;
  2. knowledge of the basic methods, techniques, tools and materials used to solve simple engineering problems related to measurement techniques and experimental data analysis;
  3. ability to analyse and interpret measurement and simulation results and draw conclusions thereof;
  4. ability to assess the usability of standard computer programs for the analysis and presentation of experimental data;
Grading policies Work during the laboratory part of the course; Reports from the laboratory exercises (reports from all exercises turned in and accepted by the teacher are required to pass the course); Test consisting of theory questions and problems to solve.
Course content LECTURE 1. Deduction and induction. Organization of the experimental research. Research planning. 2. Theory of uncertainty. Types of uncertainty. Uncertainty class. Reducing computational uncertainty. Estimating the uncertainty in practice. Propagation of uncertainty. 3. Selected topics from the probability and statistics. 4. Correlation and regression. The least squares method and the maximum likelihood method. 5. How to present the data? Plots, illustrations and tables. Report and article writing, giving talks. 6. Simple measuring devices. EXERCISES Analysis of experimental data sets. LABORATORY Students perform simple measurements and present the results in the form of reports.
Basic reference materials 
  1. Wojtatowicz T., ''Metody analizy danych doswiadczalnych. Wybrane zagadnienia'', skrypt IF PL, Lódz 1998.
  2. Brandt S. ''Analiza danych'', PWN, Warszawa 1998.
Other reference materials 
  1. Squires G.L., ''Praktyczna fizyka'', PWN, Warszawa 1992.
  2. Linnik J.W., "Metoda najmniejszych kwadratów i teoria opracowywania obserwacji", PWN, Warszawa 1962.
  3. Abramowicz H., ''Jak analizowac wyniki pomiarów'', PWN, Warszawa 1992.
Course workload
Form of classes Teaching hours
Lecture 15
Tutorial 15
Laboratory 15
Report writing 10
Preparing for the tutorials and laboratory classes 15
Preparing for the test 5
SUM : 75
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                        Updated on 
                        2020-07-17 17:42:36