Infopaket

Probability Theory and Mathematical Statistics in Sociology

ОК7

Обов’язкова дисципліна для ОП

First

2023/2024

2 Semester

5

1.1 Know modern methods for determining the integrated sample characteristics, methods for estimating the parameters of the general population. 1.2 Know the statistical and probability distributions, their characteristics and applications. 1.3 Know the methods of applying statistical criteria. 2.1 Be able to calculate the integral characteristics of the sample. 2.2 Be able to formulate statistical hypotheses. 2.3 Be able to apply statistical criteria to solve applied problems.

Full-time form

1. Know the methods of elementary mathematics. 2. Be able to work with a computer. 3. Have basic data visualization skills.

I. Probability in empirical research. Topic 1. Basic statistical sample characteristics. Topic 2. Elements of probability theory. II. Statistical hypotheses and models in sociology. Topic 3. Basic statistical estimates. Topic 4. Test of statistical hypotheses. Topic 5. Statistical criteria. Topic 6. Linear regression

Basic 1. Donchenko VS, Sydorov MV-S. Probability theory and mathematical statistics for the social sciences.- K: Taras Shevchenko National University of Kyiv, 2015, p 400. Additionally 1. Chernyak OI etc. Econometrics. Textbook / Chernyak OI; Komashko OV; Stavytsky AV; Bazhenova OV; For the order. OI Черняка. - Kyiv: Publishing and Printing Center "Kyiv University", 2010. - 359 p. 2. John A. Rice. Mathematical Statistics And Data Analysis. Duxbury Advanced Series. Available 2010 Titles Enhanced Web Assign Series. .- Cengage Learning, 2007, ISBN0534399428, 9780534399429, 603 p. 3. Elementary Statistics with R http://www.r-tutor.com/elementary-statistics 4. Medvedev MG, Pashchenko I.0. Probability theory and mathematical statistics. Textbook. - Kyiv: Lira-K Publishing House. 2008. - 536 p. 5. Litnarovich RMPobudova and research of mathematical model on sources of experimental data by methods of regression analysis. Textbook, MEGU, Rivne, 2011.-140 p

Lecture, practice session, individual work in Moodle

1. Distance course DataCamp “Introduction to R” LR 1.1, LR 1.3, LR 2.1 - 2 points / 1 point. 2. Prometheus distance learning course “Data analysis and statistical derivation in R” LR 1.1, LR 1.3, LR 2.1 - 3 points / 2 points. 3. Kr 1 with topics 1.2 LR 1.1 - 5 points / 3 points. 4. Pkr 1 with topics 1, 2 LR 1.1, LR 2.1 - 6 points / 4 points. 5. Kr 2 on topic 3, LR 1.2, LR 2.1 - 5 points / 3 points. 6. Kr 3 on topic 3, RN 1.2, RN 2.1 - 5 points / 3 points. 7. Pkr 2 with topics 3,4 and 5, LR 1.2, LR 1.3, LR 2.2, LR 2.3 - 6 points / 4 points. 8. Homework - LR 1.1, LR 1.2, LR 1.3, LR 2.1, LR 2.2, LR 2.3, total 12 points / 8 points. 9. Performances at the board - LR 1.1, LR 1.2, LR 1.3, LR 2.1, LR 2.2, LR 2.3, total 16 points / 8 points. final assessment – exam LR 1.1, LR 1.2, LR 1.3, LR 2.1, LR 2.2, LR 2.3

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