This course will enable the students to –
Course Outcomes (COs):
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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CBBA 301 |
Business Research |
Upon completion of the paper, student will: CO 101: Understand the concept of research, its classification research procedure. CO 102: Formulate research problem & Create well-structured Research design for a research problem.
CO 103: Utilize the different sampling techniques and analyze data collection tools. CO 104: Identify scaling techniques and Construct scales for data collection. CO 105: Classification and tabulation of data. CO 106: Understand the techniques of descriptive statistical analysis. |
Approach in teaching: Interactive Hours, Discussion, Tutorials, Reading assignments
Learning activities for the students: Self learning assignments, Effective questions, Giving tasks
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Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects |
Definition and concept of research, Objectives of research, Importance of research. Types of Research- Descriptive vs Analytical, Applied vs Fundamental, Quantitative vs Qualitative, Conceptual vs Empirical, Historical, Longitudinal Research. Research Approaches, Research Process.
Research Design: Meaning, Need and Characteristics of a good research design. Types of Research Design, Identification of a Research problem. Selection of a Research problem.
Hypothesis: Purpose, Characteristics, Types and criteria of hypothesis, Process of Hypothesis Testing.
Variables: Meaning and Concept, Types of variables..
Meaning of Census and Sample. Characteristics of a good Sample, Need for Sample, Methods of Sampling- Random Sampling Methods- Simple Random Sampling, Stratified Sampling, Systematic Sampling and Multi-stage Sampling. Non-Random Sampling- Judgment or Purposive Sampling, Convenience Sampling, Cluster Sampling and Sequential Sampling.
Data Collection: Data gathering instruments: Collection of Data, Primary and Secondary Data, Methods of collecting data, Sources of Secondary Data.
Measurement & Scaling: Primary scales of Measurement -Nominal, Ordinal, Interval & Ratio. Scaling techniques-paired comparison, rank order, constant sum, semantic differential, itemized ratings, Likert Scale; Questionnaire-form & design.
Measures of Central Value: Characteristics of an ideal measure- mean median, mode, Quartile and percentile. Merits, Limitations and Suitability of averages. Relationship between averages.
Measures of Dispersion: Meaning and Significance. Absolute and Relative measures of dispersion - Range, Quartile Deviation, Mean Deviation, Standard Deviation, Coefficient of Variation