Sampling Techniques Explained |Probability & Non-Probability Sampling |Research Methodology #ugcnet

Research Methodology Masterclass – Lecture 07

Welcome to Lecture 07 of the Research Methodology Masterclass! In this lecture, you'll learn everything about Sampling Techniques, including the difference between Census and Sample, Probability and Non-Probability Sampling, and Sampling Errors with simple examples.

Sampling is one of the most important concepts in research because it helps researchers collect reliable data while saving time, cost, and effort.

This lecture is designed for MLIS, BLIS, PhD scholars, UGC NET/JRF aspirants, research scholars, and students from all disciplines.

📖 In This Lecture:

✅ What is Sampling?
✅ Population, Census & Sample
✅ Why Sampling is Important
✅ Probability Sampling Methods:

Simple Random Sampling
Systematic Sampling
Stratified Sampling
Cluster Sampling
✅ Non-Probability Sampling Methods:
Convenience Sampling
Purposive Sampling
Snowball Sampling
Quota Sampling
✅ Sampling Errors
✅ Advantages & Limitations of Different Sampling Methods
✅ Library & Information Science (LIS) Examples
🎯 After Watching This Lecture, You Will Be Able To:

✔ Understand the concept of sampling.
✔ Differentiate between census and sample.
✔ Identify probability and non-probability sampling methods.
✔ Select the appropriate sampling technique for different research studies.
✔ Recognize common sampling errors and how to minimize them.

📚 Research Methodology Masterclass Playlist

Follow the complete series to master research methodology—from research basics to research design, sampling, data collection, data analysis, and report writing.

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