Courses list

Wersja polska

Course code: RTSS20248o12
Semester: 2012/2013 summer
Name: Mathematical Analysis and Engineering Statistics
Major: Agricultural and Forestry Engineering
Study Type: second cycle
Course type: compulsory
Study Semester: 1
ECTS points: 4
Hours (Lectures / Tutorials / Other): 15 / 30 / 0
Lecturer: dr hab. Wiesław Szulczewski, dr inż. Krzysztof Lejman
Language of instruction: Polish


Learning outcomes: Students acquire theoretical and practical knowledge of application of higher mathematics and statistics in solving engineering problems in the field of agricultural engineering. Identifies the method of experiment planning and the practical application of statistical tools and statistical inference. Associates and describes the practical application of the elements of field theory, scalar field, vector field, potential, potential field, gradient, rotation, divergence, Laplace transform, Fourier transform, the foundations of probability, point and interval estimation in terms of solving the basic problems of engineering farming. The student acquires the ability to apply mathematical and statistical methods to support engineering in agricultural technology. Acquires the ability to draw conclusions based on the results of statistical analyzes measuring the material. Students planning to experiment with the use of information technology. Distinguishes between mathematical and statistical methods in terms of their use in agricultural technology. Distinguishes between the concept of advanced statistical and mathematical methods. Able to choose appropriate methods and technologies to solve problems, depending on the task variables.

Competences: The student demonstrates an understanding of advanced mathematical and statistical methods for analysis and inference in research in the field of agricultural technology. Recognizes the principles of proper presentation of results and justifies the correctness of the methods used. Assess and explain the results of analyzes carried out using mathematical tools and computer. It shows the need for self-improvement and training in the use of modern information technology based on the practical applications of mathematics and statistics.

Prerequisites: higher mathematics I and higher mathematics II, foundations of computer science, statistics

Course content: Basics of probability, random variables, parametric verification of hypotheses, elements field theory, scalar field, vector field, potential, field potential, gradient, rotation, divergence. Planning an Experiment and statistical inference, data management, text and numeric, preparing data for analysis and visualization using a variety of presentation techniques, standard and modified graphical procedure, the cooperation of statistical programs of word processing and presentational software.

Recommended literature: 1. Bjorck A., Dahlquist G.: Metody numeryczne, PWN, Warszawa 1987. 2. Gewert M., Skoczylas Z.: Analiza matematyczna 2. Definicje, twierdzenia, wzory. Oficyna Wydawnicza GiS, Wrocław 2002. 3. Gewert M., Skoczylas Z.: Analiza matematyczna 2. Przykłady i zadania. Oficyna Wydawnicza GiS. Wrocław 2002. 4. Krysicki W., Włodarski L.: Analiza matematyczna w zadaniach. Część II, PWN, Warszawa 1998. 5. Fichtenholz G.M.: Rachunek różniczkowy i całkowy, t. I, II i III. PWN, Warszawa 1997. 6. Kala R. Statystyka dla przyrodników. Wyd. AR Poznań, 2002. 7. Koronacki J., Mielniczuk J.: Statystyka dla studentów kierunków technicznych i przyrodniczych. WNT, 2001. 8. Krysicki W., Włodarski L.: Analiza matematyczna w zadaniach, część I, II, PWN, Warszawa 2004. 9. Leszek W.: Badania empiryczne – wybrane zagadnienia metodyczne, Wydawnictwo Instytutu Technologii Eksploatacji, Radom, 1997 10. Łomnicki A.: Wprowadzenie do statystyki dla przyrodników. PWN, Warszawa 2003 11. Pabis S.: Metodologia i metody nauk empirycznych, PWN, Warszawa, 1985 12. Statistica PL, Tom I – Ogólne konwencje i statystyki, Tom II – Grafika, Tom III – Statystyki II, StatSoft Polska Sp. z o.o., Kraków, 1997 13. Trętowski J., Wójcik A. R.: Metodyka doświadczeń rolniczych, Wydawnictwa Uczelniane WSRP w Siedlcach, 1991 14. Volk V.: Statystyka stosowana dla inżynierów, WNT, Warszawa, 1973

Assessment methods: Assessment of learning outcomes in terms of knowledge: colloquia on exercises, oral examination Assessment of learning outcomes in literacy: assessment alone resolved statistical analysis, assessment of ability to select mathematical and computer tools for solving engineering and process simulation, evaluation of the correctness of the choice of visualization Assessing the effects of training in social skills: evaluation of methods for individual and team work, discussion of solutions and meth

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