Course Name
Mathematical Statistics
Course Overview 
Level of study	Bachelor Degree	
Workload	ECTS: 3
Total Hours: 54
Contact Hours: 36
•	Lectures: 24
•	Labs: 12
•	Seminars: 0	
Course Code		
Semester	Winter, Summer	
Prerequisites	Computer Science, Calculus	
Course Objectives	Getting knowledge in the field of mathematical statistics methods: creating mathematical models and decision-making based on experimental data	
Learning Outcomes
	By the end of the course the student will know: 
Basic statistical tool for data analysis;
The students will be able to:
Make decision and provide evidence based on experimental data
The students will have the experience in:
Performing statistical analysis and interpreting its results	
Syllabus
	Introduction to statistic
Descriptive statistic
Student’s t-test
Correlation analysis
Regression analysis
Analysis of variance	
Labs	Analyses of difference
Analyses of association	
Projects		
Assessment	Exam	
Resources	Resource type: Background textbook
Larson, Ron, Elizabeth Farber, and Elizabeth Farber. Elementary statistics: Picturing the world. No. QA276. 12. L373 2009. Pearson Prentice Hall, 2009.
Mann, Prem S. Introductory statistics. John Wiley & Sons, 2007.
Siegel, Andrew. Practical business statistics. Academic Press, 2011.	
Instructors	Ilya Ogol, http://portal.tpu.ru/SHARED/i/ILYAO	
Примечание: пример описания дисциплины можно посмотреть по ссылке: http://www.ecs.soton.ac.uk/module/COMP6233#overview