Acquiring general and specific knowledge in mathematical statistics.

After competing this course student has basic knowledge in mathematical statistics. He is capable to apply statistical tests and simulation methods in studying real-world phenomena, as well as to use statistical software R.

Basic concepts of the probability; Random variables, their distributions and numerical properties; Law of large numbers; Central limit theorem; Statistical model and the goal of mathematical statistics; Graphical representation of the data. Order statistics and variational series; Empirical distribution function; Sample mean and sample variance and their properties; Distribution parameters estimation and their properties; Interval estimation in normal and binomial model; Statistical hypothesis testing; Testing hypothesis regarding normal distribution parameters; Pearson chi-squared goodness-of-fit test. Pearson chi-squared two-sample independence test.

Exercising methods and techniques for statistical data analysis. Practical problems solving.

None.

Total assigned hours: 90

New material: 30
Elaboration and examples (recapitulation): 0

Auditory exercises: 45
Laboratory exercises: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Review and grading of calculation tasks: 5
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 0
Test: 0
Test: 5
Final exam: 5

Activity during lectures: 10
Test/test: 10
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 10
Project: 0
Final exam: 70
Requirement for taking the exam (required number of points): 0

Б, Милошевић, Основи статистике. Математички факултет, Београд, 2021; R.J. Larsen, M.L. Marx, An Introduction to Mathematical Statistics and Its Applications, Pearson Education, N. Jersey, 2006.; М.Меркле, Вероватноћа и статистика, Академска мисао, Београд, 2010.; В. Јевремовић, Вероватноћа и статистика, Математички факултет, Београд, 2009.