Course code 
07 59 1112 60 
ECTS credits 
4 
Course title in the language of instruction 
Fundamentals of Data Analysis 
Course title in Polish 
Fundamentals of Experimental Data Analysis (Podstawy analizy danych doświadczalnych) 
Course title in English 
Fundamentals of Data Analysis 
Language of instruction 
English 
Course level 
firstcycle programme 
Course coordinator 
dr inż. Ewa Pastorczak 
Course instructors 

Delivery methods and course duration 

Lecture 
Tutorials 
Laboratory 
Project 
Seminar 
Other 
Total of teaching hours during semester 
Contact hours 
20 
20 
20 


0 
60 
Elearning 
No 
No 
No 
No 
No 
No 

Assessment criteria (weightage) 
0.30 
0.40 
0.30 


0.00 


Course objective 
 To familiarize students with the theory of errors.
 To familiarize students with statistical methods of analysis of experimental data.
 To familiarize students with the preparation of measurement systems and procedures.
 To prepare students for the proper collection, analysis and presentation of experimental data.

Learning outcomes 
 Student should know how to optimally design and assemble the measuring system (FFT1A_W19, FFT1A_U18)
 Student should be able to identify sources of measurement errors (FFT1A_W19, FFT1A_W11)
 Student should be able to interpret the results of statistical tests (FFT1A_W04, FFT1A_U15)
 Student should be able to carry out statistical analysis of measurement results and errors (FFT1A_U15)
 Student should know how to properly collect and present the results of the measurements (FFT1A_U21)

Assessment methods 
The written test (LO 12)
Practical test (LO 34)
Tutorial sessions and laboratory experiments (LO 2 5)
Raports from experiments (LO 45)
Final assessment is the weighted average from theoretical test (30%), practical test (40%) and the mean
assessment of the laboratory activities (30%) 
Prerequisites 
Secondary school knowledge of mathematics 
Course content with delivery methods 
LECTURE
1. Deduction and induction. Organization of the experimental research. Research planning.
2. Error theory. Kinds of error. Uncertainty class. Applications of the Error theory.
3. Selected topics from the probability and statistics. Statistical distributions applied in physics and data analysis. Test for nonrandomness.
4. Statistical hypotheses. Parameters of the distribution. Parametric estimation  most important estimators. Selected statistical programmes.
5. Statistical hypothesis testing. Parametrical and nonparametrical tests.
6. Managing data sets. Outliers. The rule of the huge error. The Dixon, Grubbs, Youden and Cochran Tests
7. Correlation and regression. Twovariable case. Correlation and regression for more than two variables.
8. Methods of the parametrical estimation. The Least Square Method and Maximum Likelihood Method.
9. Improving measurement precision. Application of the Fourier Transform. Smoothing. Calculations. Verification of the algebraic. Extrapolation and interpolation. Commercial mathematical programms.
10. Presenting data. Charts and graphs. Selected graphical and presentation applications. Scientific publication preparing.
TUTORIALS
1. Verification of the parametric hypothesis
2. Verification of the nonparametric hypothesis
3. Correlation and regression
4. Least square method
5. Extrapolation and interpolation
LABORATORY
Students conduct simple experiments and prepare reports 
Basic reference materials 
 R. Lyman Ott, An Introduction to Statistical Methods and Data Analysis, Duxbury Press 1984
 O. Andersson, Experiment!: Planning, Implementing and Interpreting, John Wiley & Sons, 2012

Other reference materials 
 Linnik J.W., "Metoda najmniejszych kwadratów i teoria opracowywania obserwacji", PWN, Warszawa 1962.
 Gajek L., Kaluszka M., "Wnioskowanie statystyczne. Modele i metody", WNT, Warszawa 1994.
 Squires G.L., "Practical Physics", Cambridge University Press 2001.
 Abramowicz H., "Jak analizowac wyniki pomiarów", PWN, Warszawa 1992.
 J. R. Taylor, An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements, University Science Books, 1997.

Average student workload outside classroom 
27 
Comments 
Brak uwag 
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