BUSINESS RESEARCH METHODOLOGY | UNIT 3 | DSE | SEM 6 | BCOM | DU/SOL/REGULAR/NCWEB

Описание: 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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