Infopaket

Time series in astronomy

OK4

Обов’язкова дисципліна для ОП

Second

2023/2024

1 Semester

3

RN03. Apply modern theories of scientific management and business administration to organize scientific and applied research in the field of physics and/or astronomy. RN05. Carry out a phenomenological and theoretical description of the studied physical and/or astronomical phenomena, objects and processes. RN08. Present research results in the form of reports at seminars, conferences, etc., carry out a professional written description of scientific research, taking into account the requirements, purpose and target audience. RN12. Develop and apply effective algorithms and specialized software for studying models of physical and/or astronomical objects and processes, processing the results of experiments and observations

Full-time form

Successful completion of basic mathematical courses, namely mathematical analysis, linear algebra, theory of differential equations, numerical methods. Students must also have previously taken an information technology course with an emphasis on one of the programming languages ​​- C++, Python, IDL, Matlab/Octave. Students must be able to use the knowledge acquired in the numerical methods course in practice.

The course "Time Series" is designed to highlight the main results of applied statistics with an emphasis on the analysis of time series. Some of the modern methods are also considered, for which it is necessary to summarize a deep theoretical basis and make a historical overview of the development of applied statistics. The course is designed to deepen and expand knowledge of applied statistics, to obtain new systemic knowledge and skills in using methods for analyzing a scientific experiment, to create an understanding that assessing the accuracy of the results obtained is of great importance for interpreting the results of a scientific experiment. To master the approaches used for the statistical analysis of complex processes and their description from the point of view of statistics

1. Brandt S. Data Analysis. Statistical and Computational Methods for Scientists and Engineers. – Springer, 2014. – 523 p. 2. Allen R.L., Mills D.W. Signal analysis. Time, frequency, scale and structure. – Wiley, 2014. – 937 p. 3. Riley K.F., Hobson M.P., Bence S.J. Mathematical methods for physics and engineering. – Cambridge University Press, 2002. – 1233 p. 4. Chu E. Discrete and continuous Fourier transforms. – CRC Press, 2008. – 398 p. 5. Cryer J.D., Chan K.-S. Time series analysis with applications in R. – Springer, 2008. – 491 p. 6. Vaseghi S.V. Advanced digital signal processing and noise reduction. – Wiley, 2000. – 473 p. 7. Krishnan V. Probability and random processes. – Wiley, 2006. – 723 p. 8. Heumann C., Schomaker M., Shalabh. Introduction to statistics and data analysis. – Springer, 2016. – 456 p.

Lectures, Laboratory Practices

Semester assessment: 1. Tests: 2, each – 15 points (assessed based on the analysis of practical exercises to be performed on the computer, which are set at home). 2. Short independent tasks – 10 points - final assessment (in the form of an exam/complex exam, differentiated credit): Exam – 60 points - conditions for admission to the final credit at least 10 points during the semester, automatic credit if the points are more than 60.

Ukrainian