General and statistical methods of scientific research

INVEST Transversal Courses

This training program provides a comprehensive understanding of general and statistical methods used in scientific research. It covers key aspects such as the fundamentals of scientific inquiry, research design and methodology, statistical analysis, and effective presentation of research findings. Participants will engage in hands-on activities, including case studies, data analysis, and writing research reports. The program also includes a practical application module to enhance critical thinking and problem-solving skills in real-world research scenarios. Upon completion, participants will have the necessary competencies to conduct high-quality research and effectively communicate their findings.

  • ECTS: 1
  • Total hours: 12
  • Language: English
  • Mode of participation: blended
  • Max participants: 5
  • Course code: INV.TRSVL.14
  • Category: BASIC TECHNOLOGY SKILLS
Prerequisites

To enroll in this training program, participants should meet the following requirements:

  • A master's degree in a relevant field (e.g., science, engineering, social sciences, economics, or related disciplines)

  • Basic understanding of mathematical and statistical concepts

  • Familiarity with fundamental research principles and methodologies

  • Proficiency in English (for comprehension of research literature and academic writing)

  • Interest in conducting research or pursuing a PhD in a related area

How To Apply

Contact for registration: doktoranti@uard.bg 

Course registration period: 1 October – 31 October 2025

Module 1: Introduction to Scientific Research

Objective:

  • 1. Understand the purpose and importance of scientific research

  • Learn the key steps in the research process

Topics Covered:

  • Definition and Characteristics of Scientific Research

  • Types of Research: Basic, Applied, and Action Research

  • Ethical Considerations in Research

  • The Scientific Method: Observation, Hypothesis, Experimentation, Conclusion

Activities:

  • Case study discussion on real-world research problems

  • Group brainstorming on research questions

Module 2: Research Design and Methodology

Objective:

  • Understand different research designs and methodologies

  • Learn about qualitative and quantitative research methods

Topics Covered:

  • Research Design: Exploratory, Descriptive, Experimental

  • Sampling Techniques: Probability and Non-Probability Sampling

  • Data Collection Methods: Surveys, Interviews, Experiments

  • Validity and Reliability in Research

Activities:

  • Designing a small research project

  • Role-play interviews and survey design

Module 3: Statistical Methods in Research

Objective:

  • Learn basic statistical concepts and their application in research

  • Understand data analysis techniques

Topics Covered:

  • Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation

  • Inferential Statistics: Hypothesis Testing, Confidence Intervals, P-Values

  • Correlation and Regression Analysis

  • Common Statistical Software (SPSS, R, Excel)

Activities:

  • Hands-on data analysis using Excel/SPSS

  • Interpretation of statistical findings from research papers

Module 4: Writing and Presenting Research Findings

Objective:

  • Develop skills for writing research papers and reports

  • Learn how to effectively present research findings

Topics Covered:

  • Structure of a Research Paper (Introduction, Methodology, Results, Discussion)

  • Citation Styles and Referencing (APA, MLA, Chicago)

  • Creating Graphs and Tables for Data Representation

  • Presentation Skills for Research Seminars

Activities:

  • Writing a short research report

  • Presenting findings using PowerPoint

Module 5: Practical Application and Case Studies

Objective:

  • Apply knowledge gained to real-world research scenarios

  • Understand how research contributes to decision-making

Topics Covered:

  • Case Studies in Scientific Research

  • Critical Analysis of Research Papers

  • The Role of Research in Policy and Industry

Activities:

  • Group discussion on a published research paper

  • Simulation of a research study proposal

Module 6: Using AI in Scientific Research

Objective:

  • Understand how artificial intelligence (AI) can enhance scientific research

  • Learn about AI-powered tools for data analysis and literature review

Topics Covered: 

  • Introduction to AI in Research: Opportunities and Challenges

  • AI for Literature Review and Information Extraction (e.g., AI-based search engines, NLP tools)

  • Machine Learning for Data Analysis: Applications in Research

  • AI-powered Writing Assistants and Automated Data Interpretation

  • Ethical Considerations in AI-assisted Research

Activities: 

  • Hands-on session using AI tools for literature review (e.g., ChatGPT, Semantic Scholar, Elicit)

  • Practical demonstration of machine learning applications in data analysis

  • Ethical discussion on AI's role in research integrity and bias mitigation

Reading material: 

  1. Creswell, J. W. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.

  2. Babbie, E. R. (2020). The Practice of Social Research (15th ed.). Cengage Learning.

  3. Field, A. (2017). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE Publications.

  4. Bryman, A. (2016). Social Research Methods (5th ed.). Oxford University Press.

  5. Montgomery, D. C. (2020). Design and Analysis of Experiments (10th ed.). Wiley.

  6. Silverman, D. (2020). Interpreting Qualitative Data (6th ed.). SAGE Publications.

  7. Cohen, L., Manion, L., & Morrison, K. (2018). Research Methods in Education (8th ed.). Routledge.

  8. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis (8th ed.). Cengage Learning.

  9. Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson.

  10. Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). SAGE Publications.

 

Video resources 

  • Research Methodology Lecture Series (Episode 1): This lecture by Dr. Muhammad Imran Qureshi introduces fundamental concepts of research methodology, covering essential aspects of conducting scientific research. YouTube

  • Statistical Data Analysis | Statistical Data Science | Part 1: This video offers an introduction to statistical data analysis, emphasizing its significance in data science and research contexts. YouTube

Participants' progress and understanding will be assessed through a combination of the following evaluation methods:

  • Quizzes and Assignments: Periodic quizzes and short assignments to assess comprehension of key concepts.

  • Practical Exercises: Hands-on activities such as data analysis, survey design, and research project planning.

  • Research Proposal Development: Participants will be required to develop a research proposal demonstrating their understanding of research design and methodology.

  • Final Project: Conducting a mini-research study, including data collection, analysis, and reporting findings.

  • Oral Presentation: Presentation of research findings in a seminar-style setting to assess communication and presentation skills.

  • Peer and Instructor Feedback: Constructive feedback from peers and instructors to enhance learning and critical thinking.

  • Attendance and Participation: Active participation in discussions, group work, and case studies.

  • Final Examination: A written exam covering theoretical and practical aspects of research methods and statistics.

Participants who successfully complete all assessments will receive a certificate of completion.

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