logo
COURSE INFORMATION
Course Title: RESEARCH METHODS IN BUSINESS ANALYTICS
Code Course Type Regular Semester Theory Practice Lab Credits ECTS
BIDS 401 A 1 3 0 2 3 8
Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature) Assoc.Prof.Dr. Nargiza Alymkulova nalymkulova@epoka.edu.al
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours: Assoc.Prof.Dr. Nargiza Alymkulova nalymkulova@epoka.edu.al , Monday 15:00-16:30; Thursday 10:30-12:00.
Second Course Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours: NA
Language: English
Compulsory/Elective: Compulsory
Study program: (the study for which this course is offered) Master of Science in Business Intelligence and Data Science
Classroom and Meeting Time: E-B32, Mondays 18.00-20.45
Teaching Assistant(s) and Office Hours: NA
Code of Ethics: Code of Ethics of EPOKA University
Regulation of EPOKA University "On Student Discipline"
Attendance Requirement: 60 %
Course Description: The course will teach the fundamentals of how to conduct a literature review to identify research objectives and questions, how to justify research methods for the analysis of research objectives and questions, including qualitative and quantitative research methods. This course will cover research methods and data analysis tools. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods, and surveys; statistical methods, including hypothesis testing, regression; and reporting.
Course Objectives: At the end of the semester, students will be able to read and analyze published research studies in business, prepare written proposals for their research topics, and devise and conduct research studies for their theses and projects.
BASIC CONCEPTS OF THE COURSE
1 The nature and importance of business research
2 The fundamental concepts of business research methods that are useful for applying qualitative and quantitative research methods
3 Different types of business research methods and their applications
COURSE OUTLINE
Week Topics
1 Introduction and Syllabus Review. The nature of business and management research. This lecture outlines the nature of research and, more specifically, of business and management research. The basic versus applied research and relevance debates are considered and advice offered regarding keeping a reflective diary or notebook. The lecture concludes with an overview of the purpose and structure of the course. (Ch.1, pp. 35-58).
2 Formulating and clarifying the research topic. The lecture will assist students in the generation of ideas, which will help them to choose a suitable research topic, and offers advice on what makes a good research topic. After their idea has been generated and refined, the lecture discusses how to turn this idea into clear research question(s) and objectives. (Ch. 2, pp. 59-104).
3 Critically reviewing the literature. The importance of the critical literature review to students’ research will be discussed in the lecture. This class outlines what a critical review needs to include and the range of secondary and primary literature sources available. It explains the purpose of reviewing the literature, discusses a range of search strategies and contains advice on how to plan and undertake a search and to write the review. The processes of identifying key words and searching using online databases and the Internet are outlined. It also offers advice on how to record items and to evaluate their relevance as well as discussing plagiarism. (Ch. 3, pp.105-160).
4 Understanding research philosophies and approaches. The lecture will address the issue of understanding different research philosophies including positivism, critical realism, interpretivism, post modernism and pragmatism. Within this, the functionalist, interpretive, radical humanist and radical structuralist paradigms are discussed. Deductive, inductive, abductive and retroductive approaches to theory development are also considered. (Ch. 4, pp. 161-203).
5 Formulating the research design. Negotiating access and research ethics. The lecture will explore the process of research design. As part of this, the methodological choice of quantitative, qualitative or mixed methods is considered. A variety of research strategies are explored and longitudinal and cross-sectional time horizons discussed. Consideration is given to the implications of design choice for the credibility of students’ research findings and conclusions. (ch. 5, pp. 205-264). Furthermore, Issues related to gaining access and to research ethics will be explored in this lecture. It offers advice on how to gain physical and cognitive access both to organisations and to individuals using both traditional and Internet-mediated strategies. Potential ethical issues are discussed in relation to each stage of the research process and different data collection methods. Issues of data protection and data management are also introduced. (Ch.6, pp. 265-324).
6 Selecting samples; Using secondary data. The lecture considers why sampling is necessary and looks at issues of sample size and likely response rates for both probability and non-probability samples. Advice on how to relate the choice of sampling techniques to the research topic is given, and the techniques for assessing the representativeness of those who respond are discussed. Furthermore, the use of secondary data is discussed which introduces the variety of data that are likely to be available and suggests ways in which they can be used. The advantages and disadvantages of secondary data are discussed, and a range of techniques for locating these data is suggested. (Ch.7, pp.265-324; Ch.8, pp. 325-370).
7 Collecting primary data through observation; Collecting primary data using research interviews; questionnaires. The lecture is concerned with collecting data through observation. Three observation methods are presented and discussed: participant observation, structured observation and Internet-mediated observation. Types of research interview are outlined and their appropriateness discussed. The use of both self-completed and interviewer-completed questionnaires and their advantages and disadvantages explored. Particular attention is again given to ensuring that the data collected are both reliable and valid. (Ch. 9, pp. 411-466; Ch. 10, pp.467-534; Ch. 11, pp. 535-596).
8 Analyzing quantitative data; The lecture outlines and illustrates the main issues that are needed to be considered when preparing data for quantitative analysis and when analysing these data by computer. Different types of data are defined, and advice is given on how to categorise and code text and visual data and create a data matrix and to code data. Practical advice is also offered on the analysis of these data using computerised analysis software. The most appropriate diagrams to explore and illustrate data are discussed, and suggestions are made about the most appropriate statistics to use, to describe data, to explore relationships and to examine trends. (Ch. 12, pp. 597-668).
9 Midterm exam.
10 Analyzing qualitative data; Writing and presenting a research report. The nature of qualitative data and analysis, and issues associated with transcription, are discussed. The lecture outlines and briefly evaluates a number of techniques to analyse data qualitatively. The lecture will introduce with the structure, content and style of their final project report (dissertation) and any associated oral and poster presentations. Differences between consultancy (management) reports and project reports (dissertations) are outlined. Above all, the lecture encourages students to see writing as an intrinsic part of the research process. (Ch. 13, pp. 669-738; Ch. 14, pp. 739-786).
11 Presentation of the research report
12 Presentation of the research report
13 Research proposal presentations
14 Research proposal presentations
Prerequisite(s):
Textbook(s): Saunders,M.N.K., Lewis, P., and Thornhill, A. (2023). Research Methods for Business Students. 9th Ed. New York: Pearson.
Additional Literature: Hair,J.F., Page,M., and Brunsveld, N. (2020). Essentials of Business Research Methods. 4th edition, New York, Routledge.
Laboratory Work: NA
Computer Usage: Internet during class
Others: No
COURSE LEARNING OUTCOMES
1 to be able to comprehend scientific research methodology concepts for business research
2 to be able prepare a research proposal for a business research problem
3 to be able to read and critically discuss research papers in business
COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES
(Blank : no contribution, 1: least contribution ... 5: highest contribution)
No Program Competencies Cont.
Master of Science in Business Intelligence and Data Science Program
1 Demonstrate understanding the value of data driven decision making. 2
2 Graduates will acquire the ability to make informed decisions based on data analysis and interpretation. 4
3 Identify the basic concepts that underpin today’s organizational IT infrastructures, such as concepts of databases, information systems, operations and processes, cloud computing, data warehousing and Big Data, Data Mining and Machine Learning. 2
4 Students will develop advanced skills in data analysis techniques, including statistical analysis, data mining, data visualization, and predictive modeling. 5
5 Apply data mining/analytics (statistical and machine-learning) in order to solve real-world business problems. 3
6 Develop skills related to data analytics pipeline from collection, processing, analysis and interpretation 3
7 Graduates will develop strong communication skills to effectively present complex data analysis findings to diverse stakeholders. 5
8 Effectively communicate to top management the results and implications arising from data analytics, security risk assessments, and emerging technologies. 5
9 Demonstrate professionalism and leadership by taking initiatives within their domain of responsibility while working effectively with other team members. 4
10 The program offers practical training and exposure to industry-standard software and tools used in business intelligence and data analysis. 3
COURSE EVALUATION METHOD
Method Quantity Percentage
Midterm Exam(s)
1
20
Presentation
1
5
Project
1
15
Term Paper
1
20
Final Exam
1
30
Other
1
10
Total Percent: 100%
ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)
Activities Quantity Duration(Hours) Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 15 15
Assignments 1 20 20
Final examination 1 15 15
Other 1 41.5 41.5
Total Work Load:
187.5
Total Work Load/25(h):
7.5
ECTS Credit of the Course:
8
CONCLUDING REMARKS BY THE COURSE LECTURER

At the end of each semester, the lecturer submits opinions, recommendations, observations, limitations, reservations related to the conduct of the said course during the academic year. This course will firmly adhere to the university code of conduct and ethical standards. Academic dishonesty includes representing another’s work as own work, falsification, violation of test conditions, plagiarism, etc. Students caught engaging in any academically dishonest behavior will receive a failing grade. Guidelines on Research Article Presentation (project) and on Research Proposal with respective deadlines are uploaded on the Google Classroom. For Research Article Presentations (project) submission deadline is January 26, 2026 and for report submission of research proposal is February 2, 2026. All assignments to be prepared within APA. For detailed information, refer to the Publication Manual of the American Psychological Association (7th ed.), http://www.apastyle.org/. Those assignments which will be sent as e-mail attachments or sent to the system after deadline will not be accepted.
2014 - 2025 © Epoka University, ICTC Office