.
Mathematics and Informatics
Study Course Description
Course Description Statuss:Approved
Course Description Version:4.00
Study Course Accepted:03.10.2022 15:57:46
| Study Course Information | |||||||||
| Course Code: | FK_006 | LQF level: | Level 7 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Physics; Medical Physics | Target Audience: | Pharmacy | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Jevgenijs Proskurins | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Department of Physics | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Riga, 26a Anninmuizas boulevard, 1st floor, Rooms No 147 a and b, fizika rsu[pnkts]lv, +371 67061539 | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 2 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 4 | ||||
| Classes (count) | 14 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 28 | ||||
| Total Contact Hours | 32 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Anatomy, physiology, biomechanics. | ||||||||
| Objective: | To supplement the students knowledge, skills and abilities for skiing and skating healthy effects on the body, to learn training techniques and skills in practical class organizing. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Security equipment for working with a computer, mathematical programs, function limit. | Classes | 1.00 | laboratory | |||||
| 2 | Derivative of a function, derivative of a multi-argument function, differentials, equator. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | laboratory | |||||||
| 3 | Applications of differentials in mathematics, physics, chemistry. | Classes | 1.00 | laboratory | |||||
| 4 | Spreadsheets. Working with Excel 2010. Descriptive statistics. | Classes | 2.00 | laboratory | |||||
| 5 | Colloquium on previously learned topics. | Classes | 1.00 | laboratory | |||||
| 6 | Correlation analysis, regression line, null hypothesis. | Classes | 1.00 | laboratory | |||||
| 7 | Indefinite integral. | Classes | 1.00 | laboratory | |||||
| 8 | Definite integral. | Classes | 1.00 | laboratory | |||||
| 9 | Integral applications. | Classes | 1.00 | laboratory | |||||
| 10 | Differential equations, their compilation and applications in physics, chemistry, pharmacy. | Classes | 2.00 | laboratory | |||||
| 11 | Colloquium. | Classes | 1.00 | laboratory | |||||
| 12 | Repetition, combination of different programs. | Classes | 1.00 | laboratory | |||||
| 13 | Introduction to mathematics and computer science. | Lectures | 1.00 | auditorium | |||||
| Assessment | |||||||||
| Unaided Work: | Independently acquire a variety of topics of the course from the literature resources, solve assigned tasks. | ||||||||
| Assessment Criteria: | Students participation in classes, individual performance of tasks in the seminar and the result in the colloquium are assessed, in total this makes up 50% of the assessment, the other 50% is made up by the assessment in the exam. The exam consists of multiple choice test questions. | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | As a result of the course acquisition students gain basic knowledge in mathematical analysis and probability theory, statistics, computer science and computer theory. Must master the terminology of higher mathematics and get an idea of the set of applied mathematical methods. | ||||||||
| Skills: | As a result of study course acquisition, students will be able to solve higher mathematics problems, perform approximate calculations with the help of a computer, perform statistical data processing, construct graphs, choose an appropriate method for data processing, use a mathematical model to study natural processes. | ||||||||
| Competencies: | Make decisions about the use of appropriate mathematical methods in the specific situation. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | N.Brāzma, A.Brigmane, A.Krastiņš, J.Rāts. Augstākā matemātika. Rīga, Zvaigzne, 1970. – 545lpp. (akceptējams izdevums) | ||||||||
| Additional Reading | |||||||||
| 1 | I Arhipova, S. Bāliņa. Statistika ar Microsoft Excel ikvienam. Datorzinību centrs, 1999. – 2 daļas | ||||||||
| 2 | U. Teibe, U. Berķis Varbūtību teorijas un matemātiskās statistikas elementi medicīnas studentiem. Rīga, 2001., 88 lpp. | ||||||||
| Other Information Sources | |||||||||
| 1 | dažādas matemātikas programmas internetā kā quickmath.com., mathcad, wolframalpha u.c. | ||||||||
