| Lesson Code | Course Name | Class | Credit | Lesson Time | Weekly Lesson Hours (Theoretical) | Weekly Lesson Hours (Practice) | Weekly Class Hours (Laboratory) |
|---|---|---|---|---|---|---|---|
| KMKZM 4378 | Modern Problems in Applied Mathematics | төртінші курс | 7 | 210 | 1 | 4 |
The subject introduces students to one of the most modern areas of stochastic analysis
- the basics of the theory of random processes and their most important applications.
Students are used to studying the knowledge they have acquired and creating problems
for studying statistical hypotheses in their scientific work. Using the appropriate theory
of the field of mathematics, they create mathematical models based on the choice of
the optimal (analytical, quantitative, experimental) method of solving a theoretical or
practical problem..
Group work, discussion, blitz-questions, critical thinking, brainstorming, case study, development teaching method, poster protection, jigsaw method, creative teaching methods, modular teaching technology.
The teacher of the subject can change the teaching methods, forms, type of control and amount of time of introduction of specialized adaptation subjects (modules) for students with disabilities in cooperation with structural departments.
| 1 | Apply the theoretical knowledge gained in fundamental mathematics to the description of processes and phenomena in various fields of mathematics(LO6); |
| 2 | Uses methods of mathematical modeling to solve fundamental and applied practical problems(LO 8); |
| 3 | Uses theoretical and mathematical-statistical methods in the study of problems in various areas of mathematics;(LO 10); |
| 4 | - Competently solves with the help of computer programs when solving practical problems in various areas of mathematics(LO11); |
| Haftalık Konu | Evaluation Method | |
|---|---|---|
| 1 | Data and their types. Preliminary data analysis. Sampling method. General set and sample. Statistical distribution of the sample. Quantitative characteristics of the sample. Confidence interval. Normal (Gaussian) distribution | презентация |
| 2 | Errors made during the verification of statistical assumptions. Statistical criteria and their types | презентация |
| 3 | Quantitative data: two independent groups. Unpaired or independent (two-sample) Student's t-test. Fisher's F test (comparison of two variances; F-test). Mann-Whitney U test (Mann-Whitney U test) | Жазбаша |
| 4 | Quantitative data: two dependent groups. Student's paired t-test. | Жазбаша |
| 5 | Wilcoxon's T-sign rank criterion. (Wilcoxon test) | презентация |
| 6 | Z characters criterion | презентация |
| 7 | Quantitative data: more than two groups. Analysis of variance. One-factor variance | Жазбаша |
| 8 | Comparison of several groups: Kruskal-Wallis criterion. | презентация |
| 9 | Two independent groups: Pearson's Chi-square test. Fisher's exact test (Fisher's exact test) | Жазбаша |
| 10 | Two dependent groups: Mc Nemar criterion. | Жазбаша |
| 11 | More than two groups. Pearson's Chi-Square Test: Large Correlation Tables. | Жазбаша |
| 12 | Viability analysis. Censored and uncensored data. Assessment of viability. Kaplan-Meier method. The viability curve. Confidence interval of viability. Comparison of two viability curves. Log-rank criterion (Log - rank.test). or logarithmic rank criterion. Yates correction. | презентация |
| 13 | Correlation analysis. Pearson's correlation coefficient. Statistical significance of correlation. Pearson's hypothesis test criterion for the significance of the correlation coefficient. | презентация |
| 14 | Spearman's Rank Correlation Coefficient Properties of Spearman's Rank Correlation Coefficient and Hypothesis Testing of Correlation Coefficient Significance | презентация |
| 15 | Regression analysis. Linear regression analysis. Regression equation. Linear regression equation. The method of least squares. Evaluation of the significance of coefficients of the regression equation. Evaluation of the quality of the regression | Жазбаша |
| PÇ1 | PÇ2 | PÇ3 | PÇ4 | PÇ5 | PÇ6 | PÇ7 | PÇ8 | PÇ9 | PÇ10 | PÇ11 |
|---|
| Textbook / Material / Recommended Resources | ||
|---|---|---|
| 1 | 1. Tokbergenov J.B., Olasılık teorisi ve matematiksel istatistik Ders Kitabı-Almatı: ATU, 2016.-159p. http://rmebrk.kz | |
| 2 | 2. Tleukeev E.D., Olasılık teorisi için problem çözme, ders kitabı, Türkistan: Ahmet Yesevi adını taşıyan Kazak-Türk Üniversitesi, Turan yayınevi. 2020 - 152 sayfa. | |
| 3 | 3. K.Zh.Nazarova, M.D. Koshanova, E.D. Tleukeev, olasılık teorisi ve matematiksel istatistiğin unsurları konusunda bir dizi bireysel görev, Türkistan: Ahmet Yesevi adını taşıyan Kazak-Türk Üniversitesi Turan Yayınevi. 2020 - 164 sayfa. | |
| 4 | 4. Tleukeev E.D., Matematiksel istatistik, ders kitabı, Türkistan: Ahmet Yesevi adını taşıyan Kazak-Türk Üniversitesi, Turan yayınevi. 2020 - 120 sayfa. |