Main Menu
apply now
apply now
Facebook X-twitter Youtube Linkedin Instagram
Main Menu
01 uol logo tagline lockup
Main Menu
Flyout Menu

GD530 – Qualitative & Quantitative Research Methods

Master of Science in Green and Digital Management

Return to the program

Core Course

GD530 – Qualitative & Quantitative Research Methods

Course Unit Code: GD530

Type Of Unit: Core

Level of Course Unit: Second cycle

Year of Study: First/second year

Semester: On demand

Number of ECTS Credits: 9

Class Contact Hours: 35

Mode of Delivery

Face to Face

Prerequisites

None

empty chairs tables room vintage retro tone (1)

The objective of this course is to introduce the fundamental concepts and tools of qualitative methods and statistics and to provide the appropriate theoretical and practical skills necessary for collecting, analyzing, and interpreting data to conduct research and data analysis.

Learning Outcomes

  • Identify the different types of business problems that can be addressed through quantitative and qualitative research.
  • Apply the steps involved in the qualitative research process to solve specific business problems.
  • Develop questionnaires that increase response rates and reduce biases.
  • Apply tabular, graphical, and descriptive methods in order to study and understand a variable.
  • Identify the basic concepts of probability theory and probability and sampling distribution.
  • Analyze and draw conclusions using a confidence interval and a hypothesis test.
  • Apply statistical methods in order to study and understand the relationship between two or more variables.
  • Analyze data using Microsoft Excel.

Course Features

Planned learning activities and teaching methods
Formal presentation of the basic concepts and theories with exercises In-class discussions and debates; case studies; role play; presentations
Videos and other multimedia tools; experiments Individual and team-work
Demonstration of statistical use on a computer

Assessment methods and criteria
20% Individual Class Participation
30% Individual Assignment
40% Group Project (Deadline: Final Lecture)
10% Presentation of the Group Project (Final lecture)
100% total

Language of Instruction
English

Readings

Suggested Textbooks:

1. Anderson, D.R, Sweeney D.J., Williams T.A., Camm J.D., and Cochran J.J. (2018). Essentials of Modern Business Statistics with Microsoft Office Excel. Cengage Learning.

2. Illowsky, B. and Dean, S. (2012). Collaborative Statistics. http://cnx.org/content/col10522/latest/

3. Groebner, D.F., Shannon, P.W., and Fry, P.C. (2017). Business Statistics: A Decision Making Approach. Pearson Education

4. Anderson, D.R, Sweeney D.J., and Williams T.A., (2008). Statistics for Business and Economics. Pearson Education

5. Cavusgil, T., et al (2009). Conducting Market Research for International Business (Chapter 6). Harvard Business Publishing

6. Harvard Business School Press (2006). Marketer’s Toolkit: The 10 Strategies You Need to Succeed (Chapter 3)

7. Fairfax County (2012). Survey Questionnaire Design, August

Online Reading:

Useful online materials can be found in the khan Academy webpage ( https://www.khanacademy.org):

Descriptive Statistics:
https://www.khanacademy.org/math/statistics-probability/analyzing- categorical-data
https://www.khanacademy.org/math/statistics-probability/displaying- describing-data
https://www.khanacademy.org/math/statistics-probability/summarizing- quantitative-data
https://www.khanacademy.org/math/statistics-probability/describing- relationships-quantitative-data

Introduction to Probability:
https://www.khanacademy.org/math/statistics-probability/probability-library https://www.khanacademy.org/math/statistics-probability/counting- permutations-and-combinations

Probability and Sampling Distributions:
https://www.khanacademy.org/math/statistics-probability/random-variables- stats-library
https://www.khanacademy.org/math/statistics-probability/sampling- distributions-library

Interval Estimation:
https://www.khanacademy.org/math/statistics-probability/confidence- intervals-one-sample

Hypothesis Testing:
https://www.khanacademy.org/math/statistics-probability/significance-tests- one-sample
https://www.khanacademy.org/math/statistics-probability/significance-tests- confidence-intervals-two-samples

Linear Regression:
https://www.khanacademy.org/math/probability/regression/regression- correlation/v/regression-line-example https://www.khanacademy.org/math/probability/regression/regression- correlation/v/correlation-and-causality https://www.khanacademy.org/math/statistics-probability/advanced- regression-inference-transforming

Call Center

CYPRUS

GREECE

INTERNATIONAL

Request Information Request Information ⟶

Informed Consent Form

Dear Participant,

You are invited to participate in a survey as part of the DiFiCy – Digital Transformation and FinTech: Shaping Cyprus’s Economy research project which is implemented by the University of Limassol, PwC Cyprus and Unity Growth Limited.

The project is co-funded by the European Union within the framework of the Cohesion Policy Programme “THALIA 2021-2027” through the Research and Innovation Foundation (RIF) in Cyprus [Pr. number: EXCELLENCE/0524/0568].

The study has been approved by the National Bioethics Committee of Cyprus (Approval no.: EEBK EΠ 2025.01.19 )

This project explores digital transformation and FinTech adoption in Cyprus, with a particular focus on SMEs and the broader business ecosystem. It uses a mixed-methods research design, combining survey data with interviews and case study evidence to generate evidence-based insights for policymakers and businesses.

Before deciding whether to participate, please read the following information carefully.

Purpose of Participation

The purpose of this research is to better understand the drivers, challenges, and impacts of digital transformation and FinTech adoption in Cyprus. The findings aim to support evidence-based policymaking, strengthen business practices, and contribute to innovation and economic development.

Your participation involves the following:

Completion of this survey, which takes approximately 15 minutes.

Invitation to take part in an optional interview.

Contribution to a case study or discussion session at a later stage.

Your participation is entirely voluntary, and you are free to decline or withdraw at any time without any consequences.

If you wish to withdraw from the study after submitting your responses, you may do so by contacting the Project Coordinator.

Data Confidentiality and Usage

All data collected will be handled in strict accordance with the General Data Protection Regulation (GDPR) and Cyprus Data Protection Law (125(I)/2018).

Your data will be treated confidentially, pseudonymised and anonymised, and no personally identifiable information will be disclosed. Data will be securely stored and accessed only by authorised members of the research team. In some cases, qualitative data may be processed using machine learning techniques, such as keyword identification or pattern detection, strictly to support analysis; however, all interpretation and conclusions will be made by the researchers.

Aggregated and anonymised findings derived from the data (e.g., statistical summaries, graphs, and thematic insights) may be used for dissemination activities, including scientific publications, policy reports, infographics, and training materials. These outputs will not contain any information that could directly or indirectly identify participants or their organisations.

Anonymised data may be shared publicly after a 24-month embargo period, while raw or sensitive data will not be publicly available. Access to raw or sensitive data will be granted only upon justified request and consortium approval.

Your participation in this study does not involve any risks.

On the contrary, your contribution may help improve digital and FinTech policies, support SME development and innovation strategies, and enhance the overall business environment in Cyprus.

Contact Information

If you have any questions, concerns, withdraw requests or complaints, please contact the Project Coordinator, Dr. Snezana Eminidou. Please include “DiFiCy Survey” in the subject line.

Email: snezana@uol.ac.cy

Phone number: +357 22462228

Partnership:

Thank you for your valuable contribution to this research.

The project is co-funded by the EU within the framework of the Cohesion Policy Programme “THALIA 2021-2027” through the Research and Innovation Foundation. [Pr. no. EXCELLENCE/0524/0568]. The content reflects the views of the author(s) only. The European Commission and the Managing Authority of THALIA 2021–2027 cannot be held responsible for any use which may be made of the information contained therein.