Veidlapa Nr. M-3 (8)

Course Description Status: Approved

Course Description Version: 24/25.P.1.00

Description Period: 2024./25 academic year pavasara semestris

Study Course Accepted: -

Study Course Description

Methods of Mathematical Statistics in Social Sciences

Main Study Course Information

Course Code
DN_199
Branch of Science
Mathematics
ECTS
3.00
Target Audience
Information and Communication Science; Law; Management Science; Political Science; Social Anthropology; Social Welfare and Social Work; Sociology
LQF
Level 8
Study Type And Form
Full-Time

Study Course Implementer

Course Supervisor
Andrejs Ivanovs
Structure Unit Manager
Dace Bandere
Structural Unit
Department of Doctoral Studies
Contacts

Riga, 16 Dzirciema Street, dn@rsu.lv, +371 67409120

About Study Course

Objective

To provide knowledge about the use of statistical concepts in social sciences taking into account the development of digitalisation, to independently find the necessary data, group and analyse them using appropriate methods and to develop an understanding of the practical use of the obtained data in the presentation of the obtained results in the study.

Preliminary Knowledge

Knowledge in mathematics and informatics.

Learning Outcomes

Knowledge

1.On successful completion of the study course, students are able to identify knowledge that will allow to recognise the statistical terminology and the basic methods used in various publications.

Skills

1.Upon successful completion of the study course, students will be able to Correctly identify, prepare and enter data in the IBM SPSS Statistics. Analyse and create and edit tables and charts; systematise and select appropriate methods of data processing, incl. performing statistical hypotheses testing.

Competences

1.On successful completion of the study course, students will be able to correctly interpret the most important statistical indicators and to use the acquired basic statistical methods in the study data processing.

Assessment

Individual work

Title
% from total grade
Grade
1.
Individual work
-
-
1. Creating the table with names of variables, examples of data and their corresponding measurement scales of the current or planned research. 2. Reading literature from the list of Required reading according to topics of lectures and classes. 3. Reviewing examples of descriptions of statistical methods used in scientific publications. The student's contribution to the improvement of the study process is the provision of meaningful feedback on the study course by filling out its evaluation questionnaire.

Examination

Title
% from total grade
Grade
1.
Examination
-
-
1. Creating the table with names of variables, examples of data and their corresponding measurement scales of the current or planned research. 2. Reading literature from the list of Required reading according to topics of lectures and classes. 3. Reviewing examples of descriptions of statistical methods used in scientific publications.
2.
Examination
-
-
Participation in lectures and classes, a written description of statistical analysis of own research data (100%).

Study Course Theme Plan

FULL-TIME
Part 1

  1. The role of statistics in the research process. Descriptive statistics and inferential statistics. Principles of hypothesis testing with P-value and confidence intervals.

EventType
Modality
Location
Contact hours
1.
Lecture
Off site
E-Studies platform
2

  1. Types of data and measurement scales. Normal distribution. Vast range of statistical methods.

EventType
Modality
Location
Contact hours
1.
Lecture
On site
Auditorium
2

  1. Preparing data for IBM SPSS Statistics. Descriptive statistics, inferential statistics and visualization of data for proportion analysis.

EventType
Modality
Location
Contact hours
1.
Class/Seminar
On site
Computer room
3

  1. Selection of descriptive statistics, inference statistics, and visualization for quantitative data (and data on an ordinal scale) for comparison of two or more samples.

EventType
Modality
Location
Contact hours
1.
Class/Seminar
On site
Computer room
3

  1. The use of correlation, linear regression and binary logistic regression analysis. Scale reliability analysis

EventType
Modality
Location
Contact hours
1.
Class/Seminar
On site
Computer room
3

  1. Sample size calculation in different types of research. Practical work: description of statistical methods that will be used in research.

EventType
Modality
Location
Contact hours
1.
Class/Seminar
On site
Computer room
3
Total ECTS (Creditpoints):
3.00
Contact hours:
16 Academic Hours
Final Examination:
Test

Bibliography

Required Reading

1.

Nahm, F. S. 2016. Nonparametric statistical tests for the continuous data: the basic concept and the practical use. Korean J. Anesthesiol. 69(1): 8–14. DOI: 10.4097/kjae.2016.69.1.8 (Tiešsaistē)

2.

SPSS for Social Scientists. 2009. Red Globe Press; 9th Edition.

3.

IBM SPSS for Intermediate Statistics Use and Interpretation. 2015. 5th Edition. By Nancy L. Leech, Karen C. Barrett, George A. Morgan.

4.

Field, A. 2018. Discovering Statistics using IBM SPSS Statistics. 4th Edition, Sage Publications.

Additional Reading

1.

Laerd Statistics.

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