.
Statistics
Study Course Description
Course Description Statuss:Approved
Course Description Version:1.00
Study Course Accepted:02.04.2024 15:24:55
| Study Course Information | |||||||||
| Course Code: | SZF_096 | LQF level: | Level 6 | ||||||
| Credit Points: | 2.67 | ECTS: | 4.00 | ||||||
| Branch of Science: | Economics | Target Audience: | Business Management; Marketing and Advertising | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Evija Liepa-Hazeleja | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Faculty of Social Sciences | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Dzirciema street 16, Rīga, szf rsu[pnkts]lv | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 6 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 12 | ||||
| Classes (count) | 8 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 16 | ||||
| Total Contact Hours | 28 | ||||||||
| Part-Time - Semester No.1 | |||||||||
| Lectures (count) | 4 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 8 | ||||
| Classes (count) | 5 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 10 | ||||
| Total Contact Hours | 18 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Mathematics. | ||||||||
| Objective: | To develop students’ understanding of the role of statistics in market conditions. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Concept, aims, and tasks of statistics. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 2 | Statistical observation errors. | Lectures | 1.00 | auditorium | |||||
| 3 | Identification of the general population. Determination of sample size. Sampling. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 4 | Ways of obtaining information. Types of questions. Aim of survey. | Classes | 2.00 | auditorium | |||||
| 5 | Principles of selection of grouping characteristics, formation of groups and intervals. | Lectures | 1.00 | auditorium | |||||
| 6 | Absolute and relative indices of variation. Dispersion and standard deviation. Mean and mean relative standard errors of sampling. | Lectures | 1.00 | auditorium | |||||
| 7 | Calculation of the characteristics of the selected dynamic series. | Classes | 1.00 | auditorium | |||||
| 8 | Moving average model. Time series. Trend. Seasonality. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 9 | Individual indices and co-indices. | Classes | 2.00 | auditorium | |||||
| Topic Layout (Part-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Concept, aims, and tasks of statistics. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 2 | Statistical observation errors. | Lectures | 1.00 | auditorium | |||||
| 3 | Identification of the general population. Determination of sample size. Sampling. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 4 | Ways of obtaining information. Types of questions. Aim of survey. | Classes | 2.00 | auditorium | |||||
| 5 | Principles of selection of grouping characteristics, formation of groups and intervals. | Lectures | 1.00 | auditorium | |||||
| 7 | Calculation of the characteristics of the selected dynamic series. | Classes | 1.00 | auditorium | |||||
| Assessment | |||||||||
| Unaided Work: | Home assignment, report, summaries. The purpose of writing summaries (each topic: 3 – 4 pages, excluding the title page) is to develop students’ ability to reproduce the material learned, to focus on the most important aspects of the topic, and to work with the available literature. When writing the summary, reference must be made to the literature used. The purpose of writing an individual report (8 pages, excluding the title page) is to develop students’ analytical skills, therefore it cannot be a description. Objectives of the report: to define the main problems of the topic; to evaluate alternative views; to offer one’s own opinion substantiating it. References to literature must be used when writing the report. In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal. | ||||||||
| Assessment Criteria: | The final grade (using a 10-point scale) is formed on the basis of the following assessments: attendance of lectures and seminars (5%); activity and quality of answers in seminars (15%); grades for prepared summaries (25%); independent work (25%); exam work (30%). | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | Exam (Written) | ||||||||
| Learning Outcomes | |||||||||
| Knowledge: | After the completion of the study course, students acquire knowledge about information, possibilities for its acquisition, grouping, data processing methods. | ||||||||
| Skills: | Students answer logically and reasonably the questions on the topics covered, analyse the theoretical matters discussed in the lectures; are able to perceive and systematically present in a concise way the main theoretical questions and regularities of statistics. | ||||||||
| Competencies: | Students will be able to classify populations, perform economic interpretation of matrices, explain the function research algorithm, define concepts of financial mathematics. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā: risinājumi ar SPSS un MS Excel: mācību līdzeklis. Datorzinību centrs, Rīga: 2003. 349 lpp. | ||||||||
| 2 | Krastiņš, O., Ciemiņa, I. Statistika. Rīga: LR CSP. 2003. 267 lpp. | ||||||||
| 3 | Kristapsone S. Statistiskās analīzes metodes pētījumā. Rīga: 2019. 478 lpp. | ||||||||
| 4 | Orlovska A., Jurgelāne I. Ekonomiskā statistika. RTU, Rīga: 2016. 155 lpp. | ||||||||
| 5 | Volodko I. Augstākā matemātika. I daļa. Rīga: Zvaigzne ABC, 2007. 294 lpp. | ||||||||
| 6 | Volodko I. Augstākā matemātika. II daļa. Rīga: Zvaigzne ABC, 2009. 396 lpp. | ||||||||
| Additional Reading | |||||||||
| 1 | Orlovska, A. Statistika: mācību līdzeklis. Rīga: RTU, 2004. 81 lpp. | ||||||||
| 2 | Revina I. Ekonometrija. Rīga: EuroFaculty, 2002. | ||||||||
| 3 | Donald D. Cooper, Pamela S. Schindler. Business Research Methods. McGraw-Hill, 2013. | ||||||||
| 4 | Field A. Discovering Statistics using IBM SPSS Statistics. 4th edition, 2013. | ||||||||
| 5 | Jones P. W., Smith P. Stochastic Processes. An Introduction. 3rd edition. CRC press, 2018. | ||||||||
| 6 | Нименья И.Н. Статистика. Санкт-Петербург, Издательский дом «Нева». 2004. | ||||||||
| Other Information Sources | |||||||||
| 1 | Finansu un kapitāla tirgus komisijas mājas lapa | ||||||||
| 2 | Freināts L., Voronova I. Statistikas analīzes modelis: kā investīciju stratēģijas pamats. Economics & Business. 2012, Vol. 22, p36-41. 6p., EBSCO datu bāze | ||||||||
| 3 | Centrālais statistikas birojs. Statistikas rokasgrāmata | ||||||||
| 4 | Likumi.lv, Statistikas likums | ||||||||
