Business Research Methods

Course Description:

This course provides students with a comprehensive understanding of the research process and its application in business decision-making. It equips learners with the skills to design, conduct, analyze, and report empirical research using both qualitative and quantitative approaches. Key topics include problem formulation, research design, literature review, measurement and scaling, data collection methods, hypothesis testing, and statistical analysis. Students will also gain proficiency in using research tools and software (e.g., SPSS) and develop competencies in writing and presenting research findings professionally. Ethical considerations and academic integrity are emphasized throughout the course.

Course Curriculum:

 

 

Business Research Methods – Curriculum (Module-wise)

Module 1: Introduction to Business Research

• Topics:
  • Nature and importance of research in business
  • Types of research: Basic vs. Applied, Qualitative vs. Quantitative
  • Research process overview
  • Ethical considerations in research

Module 2: Problem Definition and Research Design

• Topics:
  • Identifying and defining research problems
  • Formulating research questions and hypotheses
  • Types of research designs: Exploratory, Descriptive, Causal

Module 3: Literature Review and Theoretical Framework

• Topics:
  • Purpose and methods of literature review
  • Sources of secondary data
  • Developing a conceptual/theoretical framework

Module 4: Measurement and Scaling

• Topics:
  • Variables and their measurement
  • Scales: Nominal, Ordinal, Interval, Ratio
  • Reliability and validity of measurement instruments

Module 5: Data Collection Methods

• Topics:
  • Primary vs. Secondary data
  • Survey methods: questionnaires and interviews
  • Observation and focus groups
  • Sampling techniques and sample size determination

 

 

Module 6: Questionnaire Design and Pretesting

• Topics:
  • Principles of questionnaire construction
  • Question wording and order
  • Pretesting and pilot surveys
  • data collection

Module 7: Data Preparation and Descriptive Analysis

• Topics:
  • Data cleaning, coding, and entry
  • Descriptive statistics: mean, median, mode, standard deviation
  • Graphical presentation of data

Module 8: Hypothesis Testing and Inferential Statistics

• Topics:
  • Sampling distributions and central limit theorem
  • t-tests, chi-square tests, ANOVA
  • Correlation and regression analysis

Module 9: Advanced Statistical Techniques (Optional/Advanced)

• Topics:
  • Multivariate analysis (Factor Analysis, Cluster Analysis)
  • Use of software tools (SPSS)

Module 10: Report Writing and Presentation of Research

• Topics:
  • Structure of a research report
  • Citation and referencing (APA/MLA)
  • Visual aids and oral presentation