Data Analysis for Decision Making

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

6

Кредиты

Кто читает:

Департамент социологии

Статус:

Курс обязательный

Когда читается:

1-й курс, 1, 2 модуль

Course Syllabus

Abstract

The course aims to build competencies in effective data analysis for informed decision making in social enterprise. Students will learn fundamental principles of data analytics, statistical methods, visualization tools and modern approaches to data analysis in the context of social enterprises. Emphasis is placed on the practical application of analytical techniques to measure social impact, evaluate program effectiveness, and to make strategic decisions. The course combines theoretical foundations with practical data skills, including collecting, processing, analyzing, and interpreting data to solve social entrepreneurship problems. Students will master advanced data analysis tools, learn how to create informative visualizations, and develop skills in the ethical use of data in social entrepreneurship.

Learning Objectives

• To develop students' understanding of the role of data analysis in decision-making in social entrepreneurship and the ability to apply statistical methods to solve practical problems.
• To develop skills in data collection, processing and analysis using modern tools and technologies to assess social impact and program effectiveness.
• To teach students how to create informative data visualizations and develop analytical dashboards to support decision making in social enterprises.
• To develop critical thinking in the ethical use of data and an understanding of data protection principles in the context of working with vulnerable populations.

Expected Learning Outcomes

• Able to apply modern techniques and methods of data collection, advanced methods of processing and analysis, including the use of intelligent information and analytical systems, when solving management and research problems.
• Capable of making and implementing organizational and managerial decisions in the field of social entrepreneurship based on innovative approaches and using modern technologies .
• Able to generalize and critically evaluate scientific research in management and related fields, and carry out research projects.
• Able to apply current data analysis methods to assess socio - economic effects and risks in the implementation of projects in the field of social entrepreneurship.
• Integrates analytical tools into the decision-making processes of social enterprises to improve their effectiveness and sustainability.

Course Contents

• Topic 1. to Data-Driven Decision Making
• Topic 2. Sound decision-making policy
• Topic 3. Operationalization of the decision-making model
• Topic 4. Direct and indirect effects of the social environment
• Topic 5. Presentations
• Topic 6. Controlled influence on the model
• Topic 7. Text data as a source for decision making
• Topic 8. Multilevel models in decision making
• Topic 9. Longitudinal studies
• Topic 10. Presentations

Assessment Elements

• Final Project Review: Writing a review
  Students write a review of their colleagues' final project . This will assess their ability to critically reflect on the methodology, theoretical validity of the conclusions , and their practical significance.
• Class Participation
  Active involvement in seminars and discussions. Contributes relevant insights and asks questions.
• Final Project
  A comprehensive project combining a presentation (50%) and a written report (50%). Students will analyze a real-world dataset, applying techniques from the course.

Interim Assessment

• 2026/2027 2nd module
  0.4 * Final Project + 0.4 * Final Project Review: Writing a review + 0.2 * Class Participation

Bibliography

Recommended Core Bibliography

• Rule, A., Cointet, J.-P., Bearman, P. S., ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.inrae.fr/hal-02636957 ; Proceedings of the National Academy of Sciences of the United States of America, National Academy of Sciences, 2015, & 112 (35). (2015). Lexical shifts, substantive changes, and continuity in State of the Union discourse, 1790-2014. ISSN: 0027-8424. https://doi.org/10.1073/pnas.1512221112

Recommended Additional Bibliography

• Robert I. Kabacoff. (2015). R in Action : Data Analysis and Graphics with R: Vol. Second edition. Manning.

Authors

• KUZINER EVGENIIA NIKOLAEVNA