BUSINESS RESEARCH METHODOLOGY | UNIT 3 | DSE | SEM 6 | BCOM | DU/SOL/REGULAR/NCWEB
Автор: Idea Infusion
Загружено: 2025-05-29
Просмотров: 3492
Unit 3: Data Collection that covers all the listed subtopics in a structured and engaging way:
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📊 Unit 3: Data Collection | Research Methodology Simplified | Measurement, Scaling, Sampling & More 🎓
Welcome to another comprehensive video in our Research Methodology series! In this video, we dive deep into Unit 3: Data Collection, where we break down all the key concepts and techniques used in collecting, measuring, and analyzing data in research studies.
⏱️ Duration: 9 Hours (Theory-based)
📚 Syllabus Covered – Ideal for students, researchers, and exam aspirants!
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🎯 What You'll Learn in This Video:
📏 1. Measurement and Scaling
What is measurement in research?
Types and importance of scaling.
🔢 2. Primary Scales of Measurement
Nominal Scale – Classification without order.
Ordinal Scale – Ranking with no fixed intervals.
Interval Scale – Equal intervals without a true zero.
Ratio Scale – All features including a true zero.
📐 3. Scales for Measurement of Constructs
Likert Scale – Measuring attitudes with levels of agreement.
Semantic Differential Scale – Rating on a bipolar scale.
Staple Scale – Simplified bipolar scale with numeric values.
✅ 4. Reliability and Validity
What makes a research tool consistent (reliable) and accurate (valid)?
Types of reliability: test-retest, inter-rater, internal consistency.
Types of validity: content, criterion, construct.
📊 5. Sources of Data
Primary Data – Collected directly from the source.
Secondary Data – Already available data from previous studies, websites, reports, etc.
📝 6. Questionnaire Design
Key principles of crafting effective questionnaires.
Question types, order, clarity, and neutrality.
Use of online tools like Google Forms, SurveyMonkey, etc.
🌍 7. Census and Survey Method
Census – Data from the entire population.
Survey – Data from a selected sample.
Pros, cons, and when to use each.
🎲 8. Sampling Techniques
Probability Sampling – Random, Stratified, Systematic, Cluster.
Non-Probability Sampling – Convenience, Judgmental, Snowball, Quota.
Real-life examples and use cases.
📏 9. Sample Size Determination
Factors affecting sample size.
Importance of representativeness.
Basic methods to calculate sample size.
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📌 Why Watch This Video?
✔️ Simplified explanations with examples
✔️ Helpful for research projects, dissertations & exams
✔️ Visual aids & diagrams included
✔️ Beginner-friendly and aligned with academic syllabi
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#DataCollection #ResearchMethodology #MeasurementAndScaling #SamplingTechniques #QuestionnaireDesign #AcademicLearning #UGPGCourses #ExamPrep
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