BUSI 303b
İşletme Yönetiminde Araştırma Yöntemi
Öğretim Elemanı: Doç. Dr. Abubakar Mohammed ABUBAKAR
Dersin Amacı
A core aim of the course is to help students identify research problem, develop, and use an actionable research proposal. This course utilizes both theoretical and practical exercises to develop student’s skills in conducting field research for business entities. These skills include developing and defining research problem statements; developing research objectives; utilizing the appropriate design; the use of secondary and primary data collection and instruments; sampling methods; hypotheses testing; data analysis and interpretation.At the end of the course students should be able to: Learn the overall research process from inception to report. Formulate, create research questions and hypotheses. Use a variety of research methods through hands-on experience. Identify primary characteristics of quantitative research and qualitative research. Identify primary characteristics of primary and secondary data. Apply the basic concepts of research such as variables, sampling, reliability, and validity. Use appropriate methodological paradigms to construct research proposal.
Dersin İçeriği
WEEK 1: Introduction to business research: problem definition and developing research approach. WEEK 2: Research design WEEK 3: Qualitative research: its nature and approaches WEEK 4: Qualitative research: focus groups, interviews, and projective techniques WEEK 5: Qualitative research: data analysis WEEK 6: Quantitative research: Survey and observation techniques WEEK 7: Quantitative research: questionnaire design WEEK 8: Midterm Exam WEEK 9: Quantitative research: questionnaire design WEEK 10: Quantitative research: sampling – design and procedures WEEK 11: Quantitative research: frequency distribution, cross-tabulation, and hypothesis testing WEEK 12: Quantitative research: frequency distribution, cross-tabulation, and hypothesis testing WEEK 13: Term project WEEK 14: Term project
Dersin Ön Koşulu/ Yan Koşulu
None
Ders Kitabı / Malzemesi / Önerilen Kaynaklar
Courses related materials will be provided by the instructor via the CourseWeb system.
Akademik Dürüstlük ve Yapay Zeka
· Plagiarism will not be tolerated under any circumstances.· No late submissions will be accepted, except in very rare cases (e.g., illness withmedical report, legal etc.).· Students who are absent on an exam day must provide a legitimate excusebefore the exam. Failure to do so will result in a penalty of a grade of 0· Any form of academic dishonesty (e.g., plagiarism, intellectual property theft – including materials taken from the Internet, having others do your assignments, failing to participate in group work, etc.) will result in a penalty.· Students are expected to uphold the highest standards of academic integrity when using artificial intelligence (AI) tools. While AI resources may be used to support learning, all submitted work must reflect the student’s own understanding and effort.· Unauthorized use of AI to generate or complete assignments, or failure to properly acknowledge such use when permitted, constitutes academic misconduct.